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A blog about Technology, new invention and ways of looking.

Sovereignty has mattered since the invention of the nation state—defined by borders, laws, and taxes that apply within and without. While many have tried to define it, the core idea remains: nations or jurisdictions seek to stay in control, usually to the benefit of those within their borders.

Digital sovereignty is a relatively new concept, also difficult to define but straightforward to understand. Data and applications don’t understand borders unless they are specified in policy terms, as coded into the infrastructure.

The World Wide Web had no such restrictions at its inception. Communitarian groups such as the Electronic Frontier Foundation, service providers and hyperscalers, non-profits and businesses all embraced a model that suggested data would look after itself.

But data won’t look after itself, for several reasons. First, data is massively out of control. We generate more of it all the time, and for at least two or three decades (according to historical surveys I’ve run), most organizations haven’t fully understood their data assets. This creates inefficiency and risk—not least, widespread vulnerability to cyberattack.

Risk is probability times impact—and right now, the probabilities have shot up. Invasions, tariffs, political tensions, and more have brought new urgency. This time last year, the idea of switching off another country’s IT systems was not on the radar. Now we’re seeing it happen—including the U.S. government blocking access to services overseas.

Digital sovereignty isn’t just a European concern, though it is often framed as such. In South America for example, I am told that sovereignty is leading conversations with hyperscalers; in African countries, it is being stipulated in supplier agreements. Many jurisdictions are watching, assessing, and reviewing their stance on digital sovereignty.

As the adage goes: a crisis is a problem with no time left to solve it. Digital sovereignty was a problem in waiting—but now it’s urgent. It’s gone from being an abstract ‘right to sovereignty’ to becoming a clear and present issue, in government thinking, corporate risk and how we architect and operate our computer systems.

What does the digital sovereignty landscape look like today?

Much has changed since this time last year. Unknowns remain, but much of what was unclear this time last year is now starting to solidify. Terminology is clearer – for example talking about classification and localisation rather than generic concepts.

We’re seeing a shift from theory to practice. Governments and organizations are putting policies in place that simply didn’t exist before. For example, some countries are seeing “in-country” as a primary goal, whereas others (the UK included) are adopting a risk-based approach based on trusted locales.

We’re also seeing a shift in risk priorities. From a risk standpoint, the classic triad of confidentiality, integrity, and availability are at the heart of the digital sovereignty conversation. Historically, the focus has been much more on confidentiality, driven by concerns about the US Cloud Act: essentially, can foreign governments see my data?

This year however, availability is rising in prominence, due to geopolitics and very real concerns about data accessibility in third countries. Integrity is being talked about less from a sovereignty perspective, but is no less important as a cybercrime target—ransomware and fraud being two clear and present risks.

Thinking more broadly, digital sovereignty is not just about data, or even intellectual property, but also the brain drain. Countries don’t want all their brightest young technologists leaving university only to end up in California or some other, more attractive country. They want to keep talent at home and innovate locally, to the benefit of their own GDP.

How Are Cloud Providers Responding?

Hyperscalers are playing catch-up, still looking for ways to satisfy the letter of the law whilst ignoring (in the French sense) its spirit. It’s not enough for Microsoft or AWS to say they will do everything they can to protect a jurisdiction’s data, if they are already legally obliged to do the opposite. Legislation, in this case US legislation, calls the shots—and we all know just how fragile this is right now.

We see hyperscaler progress where they offer technology to be locally managed by a third party, rather than themselves. For example, Google’s partnership with Thales, or Microsoft with Orange, both in France (Microsoft has similar in Germany). However, these are point solutions, not part of a general standard. Meanwhile, AWS’ recent announcement about creating a local entity doesn’t solve for the problem of US over-reach, which remains a core issue.

Non-hyperscaler providers and software vendors have an increasingly significant play: Oracle and HPE offer solutions that can be deployed and managed locally for example; Broadcom/VMware and Red Hat provide technologies that locally situated, private cloud providers can host. Digital sovereignty is thus a catalyst for a redistribution of “cloud spend” across a broader pool of players.

What Can Enterprise Organizations Do About It?

First, see digital sovereignty as a core element of data and application strategy. For a nation, sovereignty means having solid borders, control over IP, GDP, and so on. That’s the goal for corporations as well—control, self-determination, and resilience.

If sovereignty isn’t seen as an element of strategy, it gets pushed down into the implementation layer, leading to inefficient architectures and duplicated effort. Far better to decide up front what data, applications and processes need to be treated as sovereign, and defining an architecture to support that.

This sets the scene for making informed provisioning decisions. Your organization may have made some big bets on key vendors or hyperscalers, but multi-platform thinking increasingly dominates: multiple public and private cloud providers, with integrated operations and management. Sovereign cloud becomes one element of a well-structured multi-platform architecture.

It is not cost-neutral to deliver on sovereignty, but the overall business value should be tangible. A sovereignty initiative should bring clear advantages, not just for itself, but through the benefits that come with better control, visibility, and efficiency.

Knowing where your data is, understanding which data matters, managing it efficiently so you’re not duplicating or fragmenting it across systems—these are valuable outcomes. In addition, ignoring these questions can lead to non-compliance or be outright illegal. Even if we don’t use terms like ‘sovereignty’, organizations need a handle on their information estate.

Organizations shouldn’t be thinking everything cloud-based needs to be sovereign, but should be building strategies and policies based on data classification, prioritization and risk. Build that picture and you can solve for the highest-priority items first—the data with the strongest classification and greatest risk. That process alone takes care of 80–90% of the problem space, avoiding making sovereignty another problem whilst solving nothing.

Where to start? Look after your own organization first

Sovereignty and systems thinking go hand in hand: it’s all about scope. In enterprise architecture or business design, the biggest mistake is boiling the ocean—trying to solve everything at once.

Instead, focus on your own sovereignty. Worry about your own organization, your own jurisdiction. Know where your own borders are. Understand who your customers are, and what their requirements are. For example, if you’re a manufacturer selling into specific countries—what do those countries require? Solve for that, not for everything else. Don’t try to plan for every possible future scenario.

Focus on what you have, what you’re responsible for, and what you need to address right now. Classify and prioritise your data assets based on real-world risk. Do that, and you’re already more than halfway toward solving digital sovereignty—with all the efficiency, control, and compliance benefits that come with it.

Digital sovereignty isn’t just regulatory, but strategic. Organizations that act now can reduce risk, improve operational clarity, and prepare for a future based on trust, compliance, and resilience.

The post Why is digital sovereignty important right now? appeared first on Gigaom.



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A blog about Technology, new invention and ways of looking.

Executive Briefing

What Happened:

A stealthy, persistent backdoor was discovered in over 16,000 Fortinet firewalls. This wasn’t a new vulnerability – it was a case of attackers exploiting a subtle part of the system (language folders) to maintain unauthorized access even after the original vulnerabilities had been patched.

What It Means:

Devices that were considered “safe” may still be compromised. Attackers had read-only access to sensitive system files via symbolic links placed on the file system – completely bypassing traditional authentication and detection. Even if a device was patched months ago, the attacker could still be in place.

Business Risk:

  • Exposure of sensitive configuration files (including VPN, admin, and user data)
  • Reputational risk if customer-facing infrastructure is compromised
  • Compliance concerns depending on industry (HIPAA, PCI, etc.)
  • Loss of control over device configurations and trust boundaries

What We’re Doing About It:

We’ve implemented a targeted remediation plan that includes firmware patching, credential resets, file system audits, and access control updates. We’ve also embedded long-term controls to monitor for persistence tactics like this in the future.

Key Takeaway For Leadership:

This isn’t about one vendor or one CVE. This is a reminder that patching is only one step in a secure operations model. We’re updating our process to include persistent threat detection on all network appliances – because attackers aren’t waiting around for the next CVE to strike.


What Happened

Attackers exploited Fortinet firewalls by planting symbolic links in language file folders. These links pointed to sensitive root-level files, which were then accessible through the SSL-VPN web interface.

The result: attackers gained read-only access to system data with no credentials and no alerts. This backdoor remained even after firmware patches – unless you knew to remove it.

FortiOS Versions That Remove the Backdoor:

  • 7.6.2
  • 7.4.7
  • 7.2.11
  • 7.0.17
  • 6.4.16

If you’re running anything older, assume compromise and act accordingly.


The Real Lesson

We tend to think of patching as a full reset. It’s not. Attackers today are persistent. They don’t just get in and move laterally – they burrow in quietly, and stay.

The real problem here wasn’t a technical flaw. It was a blind spot in operational trust: the assumption that once we patch, we’re done. That assumption is no longer safe.


Ops Resolution Plan: One-Click Runbook

Playbook: Fortinet Symlink Backdoor Remediation

Purpose:
Remediate the symlink backdoor vulnerability affecting FortiGate appliances. This includes patching, auditing, credential hygiene, and confirming removal of any persistent unauthorized access.


1. Scope Your Environment

  • Identify all Fortinet devices in use (physical or virtual).
  •  Inventory all firmware versions.
  •  Check which devices have SSL-VPN enabled.

2. Patch Firmware

Patch to the following minimum versions:

  • FortiOS 7.6.2
  • FortiOS 7.4.7
  • FortiOS 7.2.11
  • FortiOS 7.0.17
  • FortiOS 6.4.16

Steps:

  •  Download firmware from Fortinet support portal.
  •  Schedule downtime or a rolling upgrade window.
  •  Backup configuration before applying updates.
  •  Apply firmware update via GUI or CLI.

3. Post-Patch Validation

After updating:

  •  Confirm version using get system status.
  •  Verify SSL-VPN is operational if in use.
  •  Run diagnose sys flash list to confirm removal of unauthorized symlinks (Fortinet script included in new firmware should clean it up automatically).

4. Credential & Session Hygiene

  •  Force password reset for all admin accounts.
  •  Revoke and re-issue any local user credentials stored in FortiGate.
  •  Invalidate all current VPN sessions.

5. System & Config Audit

  •  Review admin account list for unknown users.
  •  Validate current config files (show full-configuration) for unexpected changes.
  •  Search filesystem for remaining symbolic links (optional):
find / -type l -ls | grep -v "/usr"

6. Monitoring and Detection

  •  Enable full logging on SSL-VPN and admin interfaces.
  •  Export logs for analysis and retention.
  •  Integrate with SIEM to alert on:
    • Unusual admin logins
    • Access to unusual web resources
    • VPN access outside expected geos

7. Harden SSL-VPN

  •  Limit external exposure (use IP allowlists or geo-fencing).
  •  Require MFA on all VPN access.
  •  Disable web-mode access unless absolutely needed.
  •  Turn off unused web components (e.g., themes, language packs).

Change Control Summary

Change Type: Security hotfix
Systems Affected: FortiGate appliances running SSL-VPN
Impact: Short interruption during firmware upgrade
Risk Level: Medium
Change Owner: [Insert name/contact]
Change Window: [Insert time]
Backout Plan: See below
Test Plan: Confirm firmware version, validate VPN access, and run post-patch audits


Rollback Plan

If upgrade causes failure:

  1. Reboot into previous firmware partition using console access.
    • Run: exec set-next-reboot primary or secondary depending on which was upgraded.
  2. Restore backed-up config (pre-patch).
  3. Disable SSL-VPN temporarily to prevent exposure while issue is investigated.
  4. Notify infosec and escalate through Fortinet support.

Final Thought

This wasn’t a missed patch. It was a failure to assume attackers would play fair.

If you’re only validating whether something is “vulnerable,” you’re missing the bigger picture. You need to ask: Could someone already be here?

Security today means shrinking the space where attackers can operate – and assuming they’re clever enough to use the edges of your system against you.

The post When Patching Isn’t Enough appeared first on Gigaom.



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AI was 2024’s hot topic, so how is it evolving? What are we seeing in AI today, and what do we expect to see in the next 12-18 months? We asked Andrew Brust, Chester Conforte, Chris Ray, Dana Hernandez, Howard Holton, Ivan McPhee, Seth Byrnes, Whit Walters, and William McKnight to weigh in. 

First off, what’s still hot? Where are AI use cases seeing success?

Chester: I see people leveraging AI beyond experimentation. People have had the opportunity to experiment, and now we’re getting to a point where true, vertical-specific use cases are being developed. I’ve been tracking healthcare closely and seeing more use-case-specific, fine-tuned models, such as the use of AI to help doctors be more present during patient conversations through auditory tools for listening and note-taking. 

I believe ‘small is the new big’—that’s the key trend, such as hematology versus pathology versus pulmonology. AI in imaging technologies isn’t new, but it’s now coming to the forefront with new models used to accelerate cancer detection. It has to be backed by a healthcare professional: AI can’t be the sole source of diagnoses. A radiologist needs to validate, verify, and confirm the findings. 

Dana: In my reports, I see AI leveraged effectively from an industry-specific perspective. For instance, vendors focused on finance and insurance are using AI for tasks like preventing financial crime and automating processes, often with specialized, smaller language models. These industry-specific AI models are a significant trend I see continuing into next year.

William: We’re seeing cycles reduced in areas like pipeline development and master data management, which are becoming more autonomous. An area gaining traction is data observability—2025 might be its year. 

Andrew: Generative AI is working well in code generation—generating SQL queries and creating natural language interfaces for querying data. That’s been effective, though it’s a bit commoditized now. 

More interesting are advancements in the data layer and architecture. For instance, Postgres has a vector database add-in, which is useful for retrieval-augmented generation (RAG) queries. I see a shift from the “wow” factor of demos to practical use, using the right models and data to reduce hallucinations and make data more accessible. Over the next two or three years, vendors will move from basic query intelligence to creating more sophisticated tools.

How are we likely to see large language models evolve? 

Whit: Globally, we’ll see AI models shaped by cultural and political values. It’s less about technical developments and more about what we want our AIs to do. Consider Elon Musk’s xAI, based on Twitter/X. It’s uncensored—quite different from Google Gemini, which tends to lecture you if you ask the wrong question. 

Different providers, geographies, and governments will tend to move either towards free-er speech, or will seek to control AI’s outputs. The difference is noticeable. Next year, we’ll see a rise in models without guardrails, which will provide more direct answers.

Ivan: There’s also a lot of focus on structured prompts. A slight change in phrasing, like using “detailed” versus “comprehensive,” can yield vastly different responses. Users need to learn how to use these tools effectively.

Whit: Indeed, prompt engineering is crucial. Depending on how words are embedded in the model, you can get drastically different answers. If you ask the AI to explain what it wrote and why, it forces it to think more deeply. We’ll see domain-trained prompting tools soon—agentic models that can help optimize prompts for better outcomes.

How is AI building on and advancing the use of data through analytics and business intelligence (BI)?

Andrew: Data is the foundation of AI. We’ve seen how generative AI over large amounts of unstructured data can lead to hallucinations, and projects are getting scrapped. We’re seeing a lot of disillusionment in the enterprise space, but progress is coming: we’re starting to see a marriage between AI and BI, beyond natural language querying. 

Semantic models exist in BI to make data more understandable and can extend to structured data. When combined, we can use these models to generate useful chatbot-like experiences, pulling answers from structured and unstructured data sources. This approach creates business-useful outputs while reducing hallucinations through contextual enhancements. This is where AI will become more grounded, and data democratization will be more effective.

Howard: Agreed. BI has yet to work perfectly for the last decade. Those producing BI often don’t understand the business, and the business doesn’t fully grasp the data, leading to friction. However, this can’t be solved by Gen AI alone, it requires a mutual understanding between both groups. Forcing data-driven approaches without this doesn’t get organizations very far.

What other challenges are you seeing that might hinder AI’s progress? 

Andrew: The euphoria over AI has diverted mindshare and budgets away from data projects, which is unfortunate. Enterprises need to see them as the same. 

Whit: There’s also the AI startup bubble—too many startups, too much funding, burning through cash without generating revenue. It feels like an unsustainable situation, and we’ll see it burst a bit next year. There’s so much churn, and keeping up has become ridiculous.

Chris: Related, I am seeing vendors build solutions to “secure” GenAI / LLMs. Penetration testing as a service (PTaaS) vendors are offering LLM-focused testing, and cloud-native application protection (CNAPP) has vendors offering controls for LLMs deployed in customer cloud accounts. I don’t think buyers have even begun to understand how to effectively use LLMs in the enterprise, yet vendors are pushing new products/services to “secure” them. This is ripe for popping, although some “LLM” security products/services will pervade. 

Seth: On the supply chain security side, vendors are starting to offer AI model analysis to identify models used in environments. It feels a bit advanced, but it’s starting to happen. 

William: Another looming factor for 2025 is the EU Data Act, which will require AI systems to be able to shut off with the click of a button. This could have a big impact on AI’s ongoing development.

The million-dollar question: how close are we to artificial general intelligence (AGI)?

Whit: AGI remains a pipe dream. We don’t understand consciousness well enough to recreate it, and simply throwing compute power at the problem won’t make something conscious—it’ll just be a simulation. 

Andrew: We can progress toward AGI, but we must stop thinking that predicting the next word is intelligence. It’s just statistical prediction—an impressive application, but not truly intelligent.

Whit: Exactly. Even when AI models “reason”, it’s not true reasoning or creativity. They’re just recombining what they’ve been trained on. It’s about how far you can push combinatorics on a given dataset.

Thanks all!

The post The evolving revolution: AI in 2025 appeared first on Gigaom.



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Depending on who you speak to, technological sovereignty is either a hot topic, or something that other organizations need to deal with. So, should it matter to you and your organization? Let’s first consider what’s driving it, not least the crystal in the solute of the US Cloud Act, which ostensibly gives the US government access to any data managed by a US provider. This spooked EU authorities and nations, as well as others who saw it as a step too far. 

Whilst this accelerated activity across Europe, Africa and other continents, moves were already afoot to preserve a level of sovereignty across three axes: data movement, local control, and what is increasingly seen as the big one – a desire for countries to develop and retain skills and innovate, rather than being passive participants in a cloud-based brain drain. 

This is impacting not just government departments and their contractors, but also suppliers to in-country companies. A couple of years ago, I spoke to a manufacturing materials organization in France that provided goods to companies in Nigeria. “What’s your biggest headache,” I asked the CIO as a conversation starter. “Sovereignty,” he said. “If I can’t show my clients how I will keep data in-country, I can’t supply my goods.”

Such themes like the Cloud Act have made cross-border data management tricky. With different countries enforcing different laws, navigating where and how your data is stored has become a significant challenge. If it matters to you, it really matters. In principle, technological sovereignty solves this, but there’s no single, clear definition. It’s a concept that’s easy to understand at a high level, but tricky to pin down.

Technological sovereignty is all about ensuring you have control over your digital assets—your data, infrastructure, and the systems that run your business. But it’s not just about knowing where your data is stored. It’s about making sure that data is handled in a way that aligns with the country’s regulations and your business strategy and values.

For organizations in Europe, the rules and regs are quite specific. The upcoming EU Data Act focuses on data sharing and access across different sectors, whilst the AI Act introduces rules around artificial intelligence systems. Together, these evolving regulations are pushing organizations to rethink their technology architectures and data management strategies.

As ever, this means changing the wheels on a moving train. Hybrid/multi-cloud environments and complex data architectures add layers of complexity, whilst artificial intelligence is transforming how we interact with and manage data. AI is a sovereignty blessing and a curse – it can both enable data to be handled more effectively, but as AI models become more sophisticated, organizations need to be even more careful about how they process data from a compliance perspective. 

So, where does this leave organizations that want the flexibility of cloud services but need to maintain control over their data? Organizations have several options:

  • Sovereign Hyper-Scalers: Over the next year, cloud giants like AWS and Azure will be rolling out sovereign cloud offerings tailored to the needs of organizations that require stricter data controls. 
  • Localized Providers: Working with local managed service providers (MSPs) can give organizations more control within their own country or region, helping them keep data close to home.
  • On-premise Solutions: This is the go-to option if you want full control. However, on-premise solutions can be costly and come with their own set of complexities. It’s about balancing control with practicality.

The likelihood is a combination of all three will be required, at least in the short-medium term. Inertia will play its part: given that it’s already a challenge to move existing workloads beyond the lower-hanging fruit into the cloud, sovereignty creates yet another series of reasons to leave them where they are, for better or worse. 

There’s a way forward for sovereignty as both a goal and a burden, centered on the word governance. Good governance is about setting clear policies for how your data and systems are managed, who has access, and how you stay compliant with regulations for both your organization and your customers. This is a business-wide responsibility: every level of your organization should be aligned on what sovereignty means for your company and how you will enforce it. 

This may sound onerous to the point of impossibility, but that is the nature of governance, compliance and risk (GRC) – the trick is to assess, prioritize and plan, building sovereignty criteria into the way the business is designed. Want to do business in certain jurisdictions? If so, you need to bake their requirements into your business policies, which can then be rolled out into your application, data and operational policies. 

Get this the other way around, and it will always be harder than necessary. However, done right, technological sovereignty can also offer a competitive advantage. Organizations with a handle on their data and systems can offer their customers more security and transparency, building trust. By embedding sovereignty into your digital strategy, you’re not just protecting your organization—you’re positioning yourself as a leader in responsible business, and building a stronger foundation for growth and innovation. 

Technological sovereignty should be a strategic priority for any organization that wants to stay ahead in today’s complex digital landscape. It’s not just about choosing the right cloud provider or investing in the latest security tools—it’s about building a long-term, business-driven strategy that ensures you stay in control of your data, wherever in the world it is.

The future of sovereignty is about balance. Balancing cloud and on-premise solutions, innovation and control, and security with flexibility. If you can get that balance right, you’ll be in a strong position to navigate whatever the digital world throws at you next.

 

The post Navigating Technological Sovereignty in the Digital Age appeared first on Gigaom.



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The ownership of the information technology infrastructure library (ITIL) has changed. As a result, the information technology service management (ITSM) market’s understanding of familiar ITIL solution certification organizations (SerView and Pink Elephant), which have been relied upon for decades, no longer exists in the same way.

ITIL Certification Has Changed

ITIL best practices have long been a staple for both vendors and users in the ITSM market. For enterprise users, ITIL has provided an impactful best practices framework to guide enterprise operations and train those at the helm of ITSM deployments and operations. For vendors serving these enterprises, ITIL solution certification provides a link between enterprises and their buyers, ensuring that solutions serve the best practice needs of buyers. Together, ITIL, in all of its iterations, has raised the bar for quality service delivery.

ITIL defines specific processes for handling IT services and is now in its fourth generation, which marks a significant change. A brief history is that:

  • ITIL was originally developed to guide the provisioning of IT services by the Central Computing and Telecommunications Agency (CCTA), a government agency in Britain.
  • ITIL 2 added definitions related to service support and delivery.
  • ITIL 3 was established a five-part service management lifecycle: service strategy, service design, service transition, service operation, and continuous improvement.
  • ITIL 4 shifted focus to demonstrate business value and digital transition of all service management functions.

While this most recent change is not a layer or new revision, the ownership rights for ITIL have moved from the government to a private entity, shifting the landscape for vendor certification and creating a change that buyers must consider as they purchase certified solutions. Pink Elephant, SerView, and now PeopleCert are the key players to consider, and buyers must understand the impact of this change.

PeopleCert’s Acquisition of AXELOS

AXELOS was established as a joint venture between the UK government and Capita plc that focused on the development of a number of best practices, including ITIL. The rights to the use of ITIL language and its process definitions have now moved from the UK government and AXELOS to PeopleCert. While this transaction closed in early 2022, it began impacting the ITSM market in the spring of 2023 and continues to be a driving factor. With the acquisition of AXELOS, all decisions related to ITIL rest in the hands of PeopleCert.

In turn, PeopleCert has redefined the ITSM solution certification landscape. It now has multiple levels of vendor solution certifications that are tagged by their branding levels of Bronze, Silver, Gold, Platinum, and Platinum Global. PeopleCert’s model is designed to assess the level of support for ITIL modules and the qualifications of the vendor solutions team. It follows two basic formulaic components for evaluating how extensively ITIL is supported within the solution and whether or not the technical team has adequate ITIL expertise. Assessments are conducted by qualified third parties who evaluate solutions using this model. Like prior certification organizations, details regarding ITIL certification are publicly available for ITSM buyers and others.

While GigaOm has not specifically evaluated price points related to this granular certification approach, vendors have expressed concern about the substantial investment that is required to participate. Some vendors, especially smaller vendors, have opted to slow the process of their move to PeopleCert’s accreditation both for budget reasons and to allow the market to absorb these changes and ensure that the model is settled for the long term.

The Acquision’s Impact on Pink Elephant

PeopleCert’s acquisition has impacted Pink Elephant, which has long been the “go-to” certifier of vendor solutions for ITIL in the North American market. With PeopleCert’s acquisition, Pink Elephant is no longer able to use ITIL in the same way. The company has certifications that remain active and in place but will expire for vendors over time. Pink Elephant is changing PinkVERIFY to shift its focus to a broader market perspective for service management that encompasses multiple best practice frameworks in addition to ITIL.

The reason for this change is that Pink Elephant views best practices holistically, being influenced by the collective perspectives of vendors, the market, and users. It is considering other best practice frameworks along with ITIL and remains open to covering any that impact ITSM and service management. Some considerations for Pink Elephant include agile development methods, DevOps, LEAN IT, ITAM, and others.

This change is no doubt confusing to the market in the short term, as PinkVERIFY has long played a role in, and been a highly visible verification organization for, ITIL. Over time, it may have a beneficial impact, providing buyers with a wider lens through which to consider their service management deployments and complementing the trend of using ITSM solutions both within IT and across the enterprise.

Implications for ITSM Buyers

The net result of ITIL’s new ownership has already created confusion. It was an abrupt change in a stable IT market segment. The understanding of what qualifies or does not qualify a vendor to claim ITIL certification for their solution moved from a known to an unknown for all buyers; vendors’ understanding was also tentative. Many solution providers have quickly shifted to adopt PeopleCert ITIL certification, but others have not.

From GigaOm’s perspective, this represents a transitory change in ITIL best practices. Time will tell how the transition continues forward. In a best-case scenario, there will be clear and concise understanding about vendor solutions and what they do and do not offer in the context of ITIL verification. At the same time, Pink Elephant’s shift to a wider scope of work will add value for some buyers, and for service management as a whole. All evidence points in the direction of better clarity long term for ITIL-certified solutions and more insight around maturity levels that further extend ITSM.

Short term, it will be a challenge for buyers to understand what they can rely upon for confirmation of their vendor choices in an ITIL best practices shop. GigaOm’s report takes this into account and provides information on solutions that have shifted to PeopleCert as well as those that worked to achieve PinkVERIFY for ITIL 4 prior to this change. It is focused on ITIL 4-certified solutions. There are many ITIL 3-certified offerings that have heavily invested in ITIL and are moving along the path to ITIL 4, and will achieve that validation coincident with the settling out of the certification landscape.

Next Steps

To learn more, take a look at GigaOm’s ITSM Key Criteria and Radar reports. These reports provide a comprehensive overview of the market, outline the criteria you’ll want to consider in a purchase decision, and evaluate how a number of vendors perform against those decision criteria.

If you’re not yet a GigaOm subscriber, sign up here.

The post How ITIL’s Ownership Transition Impacts the ITSM Market appeared first on Gigaom.



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Passwords are the keys to your digital assets: it’s how we access applications and data, as well as infrastructure and systems. Often they are characters we type in as part of a logon prompt, but they can also be hidden in code, as an application makes a call to other resources to carry out its tasks.

The management of passwords is a complex process for both operations teams and users. Unfortunately, that complexity often leads to poor password practices, making passwords a high-priority target for cybercriminals: they know that gaining access to the right credentials can give them the keys to an organization’s data kingdom. And that can lead to data breaches that compromise security, productivity, and reputation.

With the complexity of the challenge and the risk that poor password management introduces, you’d think that all IT leaders would have either found ways to address the problem or have it high on the priority list. But is that the case? Recently, I worked on the third iteration of GigaOm’s Enterprise Password Management report, and one of the things that struck me is that not everyone is taking this challenge as seriously as they should and spending time to understand why password management is hard and what tools are available to help.

Why Is Password Management So Complex?

Why is password management such an issue? There are a number of reasons.

  • The volume of passwords that must be managed and remembered is at the heart of the problem. Users have dozens of passwords, each of which typically needs to be changed regularly, often with increasing complexity, resulting in poor password practice, like weak passwords, password reuse, and poor password security.
  • Password management is tedious and time consuming. It involves dealing with forgotten passwords, discovering where there is risk, and defining and applying robust password policies. Moreover, policies and controls may need to be configured in multiple applications and systems, increasing the overhead further.
  • Password policies are difficult to enforce. Organizations need to know how good their password policies are and where they are at risk. The distributed nature of passwords makes this very difficult to grasp and difficult to address.
  • Password sharing is a common practice. When access is required to common entities—such as infrastructure, machines, and applications—for maintenance or other purposes, passwords may be shared by operations teams. Other teams may share passwords to marketing and sales tools, and users may need to gain access to resources in the event of another user’s absence. This creates headaches around practicality and security.

Benefits of Password Managers

Password managers can offer significant advantages to organizations. Benefits include:

  • Storing passwords securely: These solutions provide a secure, encrypted vault into which all passwords can be placed, enabling easier and more effective management.
  • Improving reporting: By bringing passwords under the control of one application, a password manager can assess the effectiveness and security of the passwords and whether they meet the organization’s policies. It can warn of potential risk and help guide users and operations teams to apply better controls.
  • Centralizing policy management: With a view of overall password health, a password manager can help an organization to understand the types of policies it needs to deploy and provide a central location from which to apply them. Operations teams can also gain insight into how well policies are adopted and where there may still be risk when policies are not followed.
  • Making the lives of users easier: Enterprise users often have to interact with a variety of systems and resources, potentially requiring a number of passwords for access. The use of a password manager obviates the need for multiple passwords, or at the very least, it makes using them less onerous. Password managers take the complexity out of password generation and ensure passwords meet company policy. Though enterprise password managers are typically more concerned with work-related security, some provide users with access to personal password vaults, which enables them to improve password security for themselves and their families.

Challenges of Password Managers

Despite the obvious advantages of password managers, there are potential issues to consider.

  • Eggs in one basket: This is a common concern and not unfounded: with all of an organization’s credentials in one place, compromise could be devastating. The security of the vault is hugely important, requiring robust access controls, vault encryption, resilience, and protection. Keep in mind, though, that the risk of the password manager being breached may be less than the impact of poor password management practices.
  • Change is hard: As with most changes, the move to a password manager can be difficult, typically requiring organizations to mandate change in policy and user interaction with passwords and applications. IT leaders will not only need to gain leadership buy-in to password managers but also help users to effectively use them to improve the organization’s security and their own experience. This will take time and effort—but probably less time and effort than recovering from a breach caused by poor password practices.
  • Questioning the likelihood and risk of a breach: Password theft is still one of the most common ways cyberattackers gain access. It’s why phishing attacks remain so prevalent and why there is such an investment in their continued evolution. The dozens of passwords, held by hundreds or even thousands of users, across their personal and business life, all present a potential security risk. It only takes one password breach and a bad actor can gain access to sensitive applications and data.

Without a doubt, password management is hard, and finding ways to address it is critical. If you’ve never considered adding a password manager to your security arsenal, go check out some of the vendors in the space and see what they can do for you.

Next Steps

To learn more, take a look at GigaOm’s enterprise password management Key Criteria and Radar reports. These reports provide a comprehensive view of the market, outline the criteria you’ll want to consider in a purchase decision, and evaluate how a number of vendors perform against those decision criteria.

If you’re not yet a GigaOm subscriber, sign up here.

The post Are We Taking Enterprise Password Management Seriously? appeared first on Gigaom.



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In simplistic definitions, the edge is characterized as simply moving workloads closer to end users to reduce network latency associated with clouds. While that is an important component, reducing the network latency is just a third of the process. What makes an edge is reducing compute, network, and storage-related latency.

Why is Edge in Demand?

Imagine that your cloud location is close to your end users, so the network latency is under 20 milliseconds. With the sizable footprint of cloud data centers worldwide, edge services would only really be needed for remote locations, and you would expect demand to be low. But that’s not the case; we see a lot of demand for edge solutions, mainly because of the compute and storage-related latency components.

Compute latency dictates how long it takes for a request to be processed, from provisioning a compute instance to returning the result. Storage latency represents the time required to retrieve relevant data.

The Need for Speed

To reduce compute-related latency, edge services providers offer edge-native execution environments based on technologies such as WebAssembly, a binary instruction format designed as a portable compilation target for programming languages. WebAssembly offers cold starts of under one millisecond, which is particularly important when handling large variations in traffic that the services can scale without impacting performance.

To reduce storage latency, edge solutions use key value stores, which offer very fast performance for reads and writes because the database is looking for a single key and is returning its associated value rather than navigating matrices.

Reducing network latency is not a simple endeavor either, and it can take multiple forms, which give us the terms “far edge” and “near edge.” The far edge hosts compute instances in third-party infrastructure-as-a-service providers for latency times of under 20 milliseconds. The near edge entails compute instances deployed locally and managed by the customer for negligible network latency times.

Is this speed necessary? We’ve seen multiple reports that reveal that an n-second increase in page load times leads to an X% decrease in conversions. But I don’t think this is the only reason for investing in technologies that reduce latencies and load times. Over time, the amount of data and processes associated with a web page or web service has increased considerably. If we were to keep using the same technologies, we would quickly outgrow the performance standards for modern services. I believe that building and running edge-native services future-proofs infrastructure and removes any future innovation bottlenecks.

Next Steps

To learn more, take a look at GigaOm’s edge development platforms Key Criteria and Radar reports. These reports provide a comprehensive overview of the market, outline the criteria you’ll want to consider in a purchase decision, and evaluate how a number of vendors perform against those decision criteria.

If you’re not yet a GigaOm subscriber, sign up here.

The post What Makes Something Edge Native? appeared first on Gigaom.



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As a seasoned CIO/CISO and tech industry analyst with 35 years of experience, I’ve seen my fair share of cybersecurity incidents. However, the recent CrowdStrike outage stands out due to its extensive impact across multiple sectors. Here’s a deep dive into what happened, the repercussions, and the lessons we can all learn from this incident.

Background and Initial Reaction
I started my journey in IT in the late ’80s when I wrote a piece of software called PleadPerfect. Over the years, I’ve worn many hats—engineer, architect, and executive at both large and small companies. For the last 18 years, I’ve been a CIO/CISO for organizations ranging from 8-11 figures in revenue.

When I first heard about the CrowdStrike-related outage, my initial reaction was one of deep concern. I took a moment of silence in honor of the lost hours my peers and fellow IT pros sacrificed with their families to fix a problem that should never have occurred. The lack of good QA practices shown by CrowdStrike is deeply upsetting. They should have caught this issue in testing before releasing it to the public. The fact that it affected every Windows OS since 2008 is inexcusable.

Understanding the Incident
CrowdStrike’s Falcon software is installed at the core of the OS, which is how it protects machines so effectively. However, this tight integration also causes significant problems when updates are not properly tested. The faulty update led to widespread instances of the “Blue Screen of Death” (BSOD), causing machines to crash and not automatically recover. The recovery process involved booting machines in safe mode and deleting a CrowdStrike file—a task complicated by the inability to remotely enter safe mode on every device/OS. Additionally, best practices dictate securing the boot drive with BitLocker, which requires a key to unlock and enter safe mode. These keys are often stored in systems also affected by this flaw, greatly increasing the effort and time required for recovery.

Such incidents are not uncommon in the cybersecurity industry, but this one is particularly damaging because it stems from a QA and testing issue, not a cybersecurity breach. The tight integration between Falcon and the OS made the damage far more widespread and the recovery process far more onerous.

Impact on Businesses and Services
All sectors and industries were affected, but critical infrastructure sectors were hit the hardest. Transportation (airlines), banking/financial services, and healthcare (hospitals and emergency rooms) pose the most risk to world economies when disrupted. The three biggest US airlines, as well as those around the world, experienced grounded flights and communication issues. Banks in many countries went offline, and hospital networks faced significant disruptions.

Response and Resolution
CrowdStrike’s response to the incident was swift, but I am not sure what more they can do at this point. I did not feel George Kurtz’s (the CEO) apology was “full-throated” and took sufficient responsibility for the incident. This is nobody else’s fault but CrowdStrike’s. While they have committed to helping everyone affected, they have 24,000 customers, all of whom are impacted, so they cannot give each the attention they need. Billions of dollars in damage are being done to those companies from this outage.

Lessons Learned
The key lessons from this incident are clear: Be careful where you place your trust in other companies and partners. Ensure your contracts allow you to seek damages, as that may be the only recourse in such situations. Have a comprehensive disaster recovery (DR) plan and test it regularly. The number of companies having to rebuild their backup infrastructure just to restore systems because they cannot access (or do not have) their BitLocker keys is far too great.

To better prepare for and prevent similar issues, develop and thoroughly test your recovery plans. Consider using a completely different set of security tools for backup and recovery to avoid similar attack vectors. Treat backup and recovery infrastructure as a critical business function and harden it as much as possible.

Future of Cybersecurity
Time will tell how this incident influences future cybersecurity practices and policies. Between the SolarWinds and CrowdStrike issues, both being failures of best practices by the companies themselves, something has to change.

Emerging technologies like AI and machine learning could help predict and prevent similar issues by identifying potential vulnerabilities before they become problems. However, the real fix may lie in revamping processes and possibly having independent bodies audit and certify the practices of technology companies.

Personal Insights
As someone deeply involved in the tech industry, I stay updated with the latest cybersecurity trends and threats by reading extensively, following industry developments, consuming relevant content, talking to peers, and moving out of my silo to share and learn from others.

My advice to fellow CIOs and CISOs is simple: Plan for the worst and test for the worst. If you fail to prepare for these kinds of incidents, you will be in the worst possible position when the board asks for your response.

Final Thoughts
The recent CrowdStrike outage was a wake-up call for many in the tech industry. It highlighted the vulnerabilities inherent in our interconnected world and underscored the need for robust cybersecurity measures. By learning from this incident and implementing the lessons outlined above, we can better prepare for and prevent similar issues in the future.

Stay vigilant, stay prepared, and let’s continue to fortify our defenses against the ever-evolving landscape of cybersecurity threats.

The post Navigating the CrowdStrike Outage: Insights from a Tech Industry Veteran appeared first on Gigaom.



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In our previous post, we introduced the concept of zero trust and explored why it’s becoming an essential approach to cybersecurity in today’s digital landscape. We discussed the limitations of the traditional “trust but verify” model and highlighted the key principles and benefits of embracing a zero trust philosophy.

Now that you have a solid understanding of what zero trust is and why it matters, it’s time to dive deeper into the building blocks that make up a zero trust architecture. In this post, we’ll explore the core components of zero trust and how they work together to create a robust, resilient security posture.

The Six Pillars of Zero Trust

While various frameworks and models exist for implementing zero trust, most of them share a common set of core components. These six pillars form the foundation of a comprehensive zero trust architecture:

  1. Identity: In a zero trust model, identity becomes the new perimeter. It’s essential to establish strong authentication and authorization mechanisms to ensure that only verified users and devices can access resources.
  2. Devices: Zero trust requires continuous monitoring and validation of all devices accessing the network, including IoT and BYOD devices. This pillar focuses on ensuring device health, integrity, and compliance.
  3. Network: By segmenting the network into smaller, isolated zones and enforcing granular access controls, organizations can minimize the blast radius of potential breaches and limit lateral movement.
  4. Applications: Zero trust principles extend to applications, requiring secure access, continuous monitoring, and real-time risk assessment. This pillar involves implementing application-level controls and securing communication between applications.
  5. Data: Protecting sensitive data is a core objective of zero trust. This pillar involves data classification, encryption, and access controls to ensure that data remains secure throughout its lifecycle.
  6. Infrastructure: Zero trust requires securing all infrastructure components, including cloud services, servers, and containers. This pillar focuses on hardening systems, applying security patches, and monitoring for vulnerabilities.

By addressing each of these pillars, organizations can create a comprehensive zero trust architecture that provides end-to-end security across their entire digital ecosystem.

Implementing the Zero Trust Building Blocks

Now that you understand the six pillars of zero trust, let’s explore some practical steps for implementing these building blocks in your organization.

  1. Establish strong identity and access management (IAM): Implement multi-factor authentication (MFA), single sign-on (SSO), and risk-based access policies to ensure that only verified users can access resources. Use tools like Azure Active Directory or Okta to streamline IAM processes.
  2. Implement device health and compliance checks: Use mobile device management (MDM) and endpoint protection platforms to enforce device health policies, monitor for threats, and ensure compliance with security standards. Solutions like Microsoft Intune or VMware Workspace ONE can help manage and secure devices.
  3. Segment your network: Use micro-segmentation to divide your network into smaller, isolated zones based on application, data sensitivity, or user roles. Implement software-defined networking (SDN) and network access controls (NAC) to enforce granular access policies.
  4. Secure your applications: Implement application-level controls, such as API gateways, and use tools like Cloudflare Access or Zscaler Private Access to secure application access. Regularly assess and test your applications for vulnerabilities and ensure secure communication between applications.
  5. Protect your data: Classify your data based on sensitivity, implement encryption for data at rest and in transit, and enforce strict access controls. Use data loss prevention (DLP) tools to monitor for data exfiltration and prevent unauthorized access.
  6. Harden your infrastructure: Regularly patch and update your systems, use hardened images for virtual machines and containers, and implement infrastructure as code (IaC) to ensure consistent and secure configurations. Leverage tools like Terraform or Ansible to automate infrastructure provisioning and management.

Measuring the Success of Your Zero Trust Implementation

As you implement zero trust in your organization, it’s crucial to establish metrics and key performance indicators (KPIs) to measure the success of your efforts. Some key metrics to consider include:

  • Reduction in the number of security incidents and breaches
  • Decreased time to detect and respond to threats
  • Improved compliance with industry regulations and standards
  • Increased visibility into user and device activity
  • Enhanced user experience and productivity

By regularly monitoring and reporting on these metrics, you can demonstrate the value of your zero trust initiatives and continuously improve your security posture.

Conclusion

Building a zero trust architecture is a complex and ongoing process, but by understanding the core components and implementing them systematically, you can create a robust, adaptable security posture that meets the challenges of the modern threat landscape.

Remember, zero trust is not a one-size-fits-all solution. It’s essential to tailor your approach to your organization’s unique needs, risk profile, and business objectives. Start small, focus on high-impact initiatives, and continuously iterate and improve your zero trust implementation.

In our next post, we’ll explore some real-world examples of successful zero trust implementations and share lessons learned from organizations that have embarked on their own zero trust journeys.

Until then, start evaluating your current security posture against the six pillars of zero trust and identify opportunities for improvement. The road to zero trust is long, but every step you take brings you closer to a more secure, resilient future.

Additional Resources:

Meta Description: Discover the six essential building blocks of a comprehensive zero trust architecture and learn practical steps for implementing them in your organization. From identity and device management to network segmentation and data protection, this guide covers the core components of a robust zero trust security posture.

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Welcome to our new blog series on zero trust! If you’re an IT executive trying to navigate the complex world of cybersecurity, you’re in the right place. Over the next few posts, we’re going to demystify this buzzworthy concept and show you how to make it work for your organization. No jargon, no fluff, just practical insights you can use to enhance your security posture and protect your business.

In this first post, we’ll explore why the traditional “trust but verify” approach to security is no longer enough and why zero trust is the way forward. We’ll also give you some action items to get started on your zero trust journey. But first, let’s talk about the elephant in the room: what exactly is zero trust, and why should you care?

The Problem with “Trust but Verify”

For years, the “trust but verify” model was the gold standard in cybersecurity. The idea was simple: once a user or device was authenticated and allowed into the network, they were trusted to access resources and data. This approach worked well enough when most employees worked in the office and used company-issued devices.

Times have changed, however, and the limitations of “trust but verify” have become increasingly apparent:

  • It doesn’t effectively limit the blast radius of a breach. If an attacker compromises a trusted user or device, they can move laterally within the network, accessing sensitive data and systems. The damage can be extensive and costly.
  • It’s too focused on access control alone. It doesn’t adequately address other critical areas like device security, network segmentation, and data protection. In today’s complex, distributed IT environments, this narrow focus leaves organizations vulnerable.

The bottom line is that “trust but verify” is no longer sufficient to protect against modern cyber threats. We need a more comprehensive, adaptable approach to security – and that’s where zero trust comes in.

Zero Trust: A Philosophy, Not a Product

Zero trust is a security model that assumes no user, device, or network should be trusted by default, regardless of whether they’re inside or outside the organization’s perimeter. It’s a philosophy that emphasizes continuous verification, least privilege access, and granular control over resources and data.

Now, you might be thinking, “Great, another cybersecurity buzzword to add to the pile.” And it’s true that the term “zero trust” has been co-opted by many vendors to align with their product offerings. But don’t be fooled: zero trust is not a product you can buy off the shelf. It’s a mindset, a set of principles that guide your approach to security:

  • Never trust, always verify
  • Assume breach
  • Verify explicitly
  • Use least privilege access
  • Monitor and audit continuously

By adopting these principles, organizations can create a more robust, resilient security posture that addresses the limitations of “trust but verify” and reduces the blast radius of potential breaches.

Why You Need Zero Trust

Embracing zero trust is not just about staying on top of the latest cybersecurity trends. It is a business decision that can deliver real, tangible benefits:

  • Reduced risk: By not trusting anyone or anything by default and continuously verifying access, you can significantly reduce your attack surface and limit the potential damage of a breach. This is crucial in an era where the average cost of a data breach is $4.35 million (IBM Security, 2022).
  • Improved visibility and control: Zero trust gives you granular control over who can access what and helps you spot potential threats more quickly. With better visibility into your environment, you can respond to incidents faster and more effectively.
  • Enabling digital transformation: As you adopt cloud services, implement IoT devices, and enable remote work, zero trust provides a framework for securing these new environments and use cases. It allows you to embrace innovation without compromising security.
  • Competitive advantage: By demonstrating a strong commitment to security, you can build trust with customers, partners, and regulators. In a world where data breaches make headlines almost daily, being able to showcase your robust security posture can set you apart from the competition.

Getting Started with Zero Trust

Implementing zero trust is not a one-and-done project. It’s a journey that requires a shift in mindset and a willingness to rethink traditional approaches to security. But just because it’s not easy doesn’t mean there’s nothing you can do to get started. Here are some action items you can tackle right away:

  1. Educate yourself and your team: Share this blog post with your colleagues and start a conversation about zero trust. The more everyone understands the concept, the easier it will be to implement.
  2. Assess your current security posture: Take a hard look at your existing security controls and identify gaps or weaknesses that a zero trust approach could address. This will help you prioritize your efforts and build a roadmap for implementation.
  3. Start small: Identify a specific use case or area of your environment where you can pilot zero trust principles, such as a particular application or user group. Starting small allows you to test and refine your approach before scaling up.
  4. Engage stakeholders: Zero trust is not just an IT initiative. It requires buy-in and participation from business leaders, end-users, and other stakeholders. Start talking to these groups about the benefits of zero trust and how it will impact them. Getting everyone on board early will make the transition smoother.

Wrapping Up

Adopting zero trust is a significant undertaking, but it’s one that’s well worth the effort. By embracing a philosophy of “never trust, always verify,” you can reduce your risk, improve your visibility and control, enable digital transformation, and gain a competitive edge in the market.

Over the course of this blog series, we’ll dive deeper into the key components of a zero trust architecture, explore best practices for implementation, and show you how to measure the success of your zero trust initiatives. We’ll also dispel common myths and misconceptions about zero trust and provide practical guidance for overcoming challenges along the way.

So, whether you’re just starting to explore zero trust or you’re well on your way to implementation, this series is for you. Stay tuned for our next post, where we’ll take a closer look at the building blocks of a zero trust architecture and how they work together to protect your assets and data.

In the meantime, start exploring zero trust and thinking about how it can benefit your organization. The future of security is here, and it’s time to embrace it.

Additional Resources:

The post Zero Trust 101: It’s Time to Ditch “Trust but Verify” appeared first on Gigaom.



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A stitch in time saves nine, they say, and so can receiving information in the right order.

We at GigaOm are constantly looking to make our research processes more efficient and more effective. Vendors often tell us what it’s like to work with us—we welcome these interactions and look to address every comment (so thank you for these!). We spent a good part of 2023 on driving far-reaching improvements in our processes, and we’re building on that in the knowledge that better efficiency leads to higher quality research at lower cost, as well as happier analysts and vendors!

That’s why we’re making a small yet necessary change to our briefings process. Historically, we’ve asked vendors to complete a questionnaire and/or schedule a briefing call, and we haven’t specified the order these should take place. The small tweak is to request that vendors first complete a questionnaire, THEN participate in a call to clarify details.

In practice, this means we will enforce receiving a completed questionnaire 24 hours before a scheduled briefing call. Should we not receive it within this timeframe, we will reschedule the briefing so the questionnaire can be completed and reviewed prior to the call. Analysts need time to review vendor responses before a briefing, so getting the questionnaire five minutes before won’t cut it.

As well as fostering efficiency on both sides, the broader reasons for this change are founded in our engineering-led evaluation approach, which reflects how an end-user organization might conduct an RFP process. What we do is to set out a number of decision criteria we expect products to possess, then ask for evidence to show these features are in fact present.

Briefings are actually an inefficient mechanism for delivering that information; the questionnaire is far better at giving us what we need to know to assess whether and how a product delivers on our criteria. Briefings should supplement the questionnaire, giving analysts an opportunity to ask follow-up questions about vendor responses which will cut down on unnecessary back-and-forth during fact check.

Briefings also have their own distractions. Keep in mind that we care less about market positioning and more about product capability. General briefings (outside of the research cycle) are a great place to set out strategy, have the logo slide, run through case studies, and all that. We love those general briefings, but the research cycle is the wrong moment for the big tent stuff (which often exists as a prerecorded video that we’d be happy to review, just not as part of a report briefing call).

I’ve often told vendors we’re not looking for all the bling during briefings. In the best cases, our engineers engage with your engineers about the key features of your products. We don’t need trained spokespeople as much as an honest conversation about functionality and use cases—10 minutes on a video call can clarify something that reams of marketing material, and user documentation cannot. Hence the change.

This shouldn’t add any extra time to the process—the opposite, in fact, as briefings are more productive when the questionnaire is already in place. We can reduce costly errors, decrease back-and-forth clarifications, and minimize misinterpretation (with the consequent potential backlash on AR, “how did you let them write that?”).

So, there you have it. We’ll be rolling out this change in early June for our September reports, so nothing will happen in a rush. Any questions or concerns, please do let us know—we’re constantly adjusting timeframes based on national holidays, industry conferences, and competitor cycles, and we welcome all input on events that might impact delivery.

We are looking at other ways we can improve efficiency, notably simplifying or reformatting the questionnaire, so watch this space for details—and we welcome any thoughts you may have! We also understand that logistics can be tough: we are all juggling time, resources, and people to enable research to happen.

We absolutely recognize the symbiosis between analysts and vendors, and we thoroughly appreciate the efforts made by AR teams on our behalf, to enable these interactions to happen—from familiarization with GigaOm and explaining our value, through negotiating the minefield of operational logistics! Our door is always open if you need anyone to help support your endeavors, as we work toward a win-win for all.

The post On Questionnaires and Briefings: Explaining the GigaOm Policy Change appeared first on Gigaom.



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Sit up straight! Shoulders back, chest out! We all heard these wise words about the importance of physical posture growing up. For those who did sit up straight and find themselves in positions of influence when it comes to IT, they are still hearing about the importance of posture, but in this case, it’s the importance of security posture.

Data security is an essential part of the day-to-day mission for any diligent business, but it is also a challenge because of the complexity of how we store, access, and use data while continuing to grow. Therefore, finding effective ways to secure it has been a priority, which has led to the development of data security posture management (DSPM) solutions.

What Value Does a DSPM Solution Provide?

DSPM solutions help organizations build a detailed view of their data environment and associated security risks across three key areas:

  • Discovery and classification: This is the fundamental first step, as you can’t secure what you don’t know exists. Solutions look across cloud repositories—platform as a service (PaaS), infrastructure as a service (IaaS), and software as a service (SaaS)—as well as on-premises sources to discover and classify data, looking for sensitive information that could be misused.
  • Access reviews: Monitoring who is using critical data, what they’re doing with it, and where they’re doing it from is the next step. It’s also important to track the ways in which sensitive data moves through and out of an organization. DSPM solutions review this information looking for misconfigurations, patterns, poorly configured repositories, and over-provisioned rights.
  • Risk analysis: Once the above analysis is complete, DSPM solutions present a clear proposed security posture. They highlight risks, report on compliance against security frameworks, and offer guidance on how to lower these risks. Without insight into these areas, it’s impossible to apply robust data security.

This type of analysis can be done with native tools and skilled operations teams, but DSPM solutions bring all of these actions and insights into one tool, automating the effort and providing additional intelligence along the way—often more quickly and more accurately than a human.

How Will AI Impact the DSPM Market?

The original purchase drivers of data security tools were the introduction of GDPR, the European Union regulation, and a flurry of other data privacy legislation. Organizations needed to understand their data and where it presented regulatory risk, driving an increased adoption of discovery, classification, and security tools.

It’s likely that artificial intelligence (AI) will drive a new wave of DSPM adoption. AI learning models present a range of opportunities for businesses to mine their data for new insights, creativity, and efficiency, but they also present risks. Given the wrong access to data or even access to the wrong data, AI tools can introduce a range of security and commercial business risks. For example, if tools surface information to users that they would not normally be able to access or present inaccurate information to customers and partners, this could result in negative commercial and legal impacts.

Therefore, it’s essential for organizations to take steps to ensure that the data models that AI is using are both accurate and appropriate. How do they do that? They need insight into their data and to understand when and what information AI learning models are accessing and whether that data is still valid. AI usage should have us thinking about how to ensure the quality and security of our data. DSPM may just be the answer.

Are DSPM Solutions Worth the Investment?

The reality is “it depends.” It’s useful to realize that while DSPM solutions can definitely deliver value, they are complex and come with a cost that’s more than financial. Fully adopting the technology, as well as an effective DSPM process, requires operational and cultural change. These types of changes do not come easily, so it’s important that a strong use case exists before you begin looking at DSPM.

The most important thing you should consider before adoption is the business case. Data security is fundamentally a business problem, so adopting DSPM cannot be an IT project alone; it must be part of a business process.

The strongest business case for deployment comes from organizations in heavily regulated industries, such as finance, healthcare, critical infrastructure, and pharma. These usually demand compliance with strict regulations, and businesses must demonstrate their compliance to boards, regulators, and customers.

The next most common business case is companies for which data is the business, such as those involved in data exchange and brokering. They demand the most stringent controls because any failures in security could lead to business failure.

If you’re not in one of those types of organizations, it doesn’t mean that you shouldn’t adopt a DSPM solution, but you do need to consider your business case carefully and ensure there’s buy-in from senior management before you begin a DSPM project.

Stand Up Straight, and Get your Data Security Posture Right

A good data security posture is essential to all businesses. A DSPM tool will give you the insight, guidance, and controls you need and do it more quickly and effectively than pulling together information from several different tools and resources, improving your organization’s posture more quickly and saving on costs at the same time.

So, don’t slouch, sit up straight, and improve your data security posture.

Next Steps

To learn more, take a look at GigaOm’s DSPM Key Criteria and Radar reports. These reports provide a comprehensive overview of the market, outline the criteria you’ll want to consider in a purchase decision, and evaluate how a number of vendors perform against those decision criteria.

The post Everything Your Parents Told You About Posture Is True! Even For Data Security appeared first on Gigaom.



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Embarking on an exploration of the extended detection and response (XDR) sector wasn’t just another research project for me; it was a dive back into familiar waters with an eye on how the tide has turned. Having once been part of a team at a vendor that developed an early XDR prototype, my return to this evolving domain was both nostalgic and eye-opening. The concept we toyed with in its nascent stages has burgeoned into a cybersecurity imperative, promising to redefine threat detection and response across the digital landscape.

Discovering XDR: Past and Present

My previous stint in developing an XDR prototype was imbued with the vision of creating a unified platform that could offer a panoramic view of security threats, moving beyond siloed defenses. Fast forward to my recent exploration, and it’s clear that the industry has taken this vision and run with it—molding XDR into a comprehensive solution that integrates across security layers to offer unparalleled visibility and control.

The research process was akin to piecing together a vast jigsaw puzzle. Through a blend of reading industry white papers, diving deep into knowledge-base articles, and drawing from my background, I charted the evolution of XDR from a promising prototype to a mature cybersecurity solution. This deep dive not only broadened my understanding but also reignited my enthusiasm for the potential of integrated defense mechanisms against today’s sophisticated cyberthreats.

The Adoption Challenge: Beyond Integration

The most formidable challenge that emerged in adopting XDR solutions is integration complexity—a barrier we had anticipated in the early development days and has only intensified. Organizations today face the Herculean task of intertwining their diversified security tools with an XDR platform, where each tool speaks a different digital language and adheres to distinct protocols.

However, the adoption challenges extend beyond the technical realm. There’s a strategic dissonance in aligning an organization’s security objectives with the capabilities of XDR platforms. This alignment is crucial, yet often elusive, as it demands a top-down reevaluation of security priorities, processes, and personnel readiness. Organizations must not only reconcile their current security infrastructure with an XDR system but also ensure their teams are adept at leveraging this integration to its fullest potential.

Surprises and Insights

The resurgence of AI and machine learning within XDR solutions echoed the early ambitions of prototype development. The sophistication of these technologies in predicting and mitigating threats in real time was a revelation, showcasing how far the maturation of XDR has come. Furthermore, the vibrant ecosystem of partnerships and integrations underscored XDR’s shift from a standalone solution to a collaborative security framework, a pivot that resonates deeply with the interconnected nature of digital threats today.

Reflecting on the Evolution

Since venturing into XDR prototype development, the sector’s evolution has been marked by a nuanced understanding of adoption complexities and an expansion in threat coverage. The emphasis on refining integration strategies and enhancing customization signifies a market that’s not just growing but maturing—ready to tackle the diversifying threat landscape with innovative solutions.

The journey back into the XDR landscape, juxtaposed against my early experiences, was a testament to the sector’s dynamism. As adopters navigate the complexities of integrating XDR into their security arsenals, the path ahead is illuminated by the promise of a more resilient, unified defense mechanism against cyber adversaries. The evolution of XDR from an emerging prototype to a cornerstone of modern cybersecurity strategies mirrors the sector’s readiness to confront the future—a future where the digital well-being of organizations is shielded by the robust, integrated, and intuitive capabilities of XDR platforms.

Next Steps

To learn more, take a look at GigaOm’s XDR Key Criteria and Radar reports. These reports provide a comprehensive overview of the market, outline the criteria you’ll want to consider in a purchase decision, and evaluate how a number of vendors perform against those decision criteria.

If you’re not yet a GigaOm subscriber, you can access the research using a free trial.

The post The Quest for Extended Detection and Response (XDR): Unraveling Cybersecurity’s Next Generation appeared first on Gigaom.



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Can observability deal with the IT chaos facing so many enterprises today? It’s a question worth digging into.

IT Chaos (Monitoring, Observability, and Intelligence)

IT chaos is a function of monitoring, observability, and intelligence. Yes, I added intelligence, but I’m not talking about artificial intelligence (AI)—yet. Just as monitoring has generated more data than humans can consume, observability can produce more observations than anyone can understand. The overload of observation information is particularly true when multiple observation tools come into play.

Machine learning can help, but the questions we want to answer are changing. Once, we wanted to know if services in a public cloud worked and how to merge that data with the on-premises noise. Now, the questions have changed to what to do about the observations. Automation allows restarting poorly performing items and expanding memory or computing power on demand, but you have to store the data somewhere, and storage is not free. Leading observability solutions now include real-time cost comparisons between cloud vendors. The best observability tools have financial operations (FinOps) abilities to find underused, overused, and abandoned resources in clouds (public or private).

Observability tooling has enough data to predict future states. Unfortunately, chaos theory does not help. Data at the element level does not exist at the observability level. Regression analysis, least-squares fits, and more complicated algorithms allow the prediction of chaos. The more data available, the more accurate the predictions, but storing data is costly. Vendors are addressing the issues with consumption-based licensing, lower-cost storage tiers, and other methods to deal with the wave of data needed for observability.

IT chaos will never end, but at least we can try to manage it. The new hope is generative AI (GenAI)—maybe.

Chaos, Observability, and Artificial Intelligence

The chaos function contains the steps from monitoring to observability to intelligence and requires new approaches to answer questions. Monitoring tells us the state of items, observability can create relationships and provide a meta view of the elements, and intelligent questions are possible with the help of GenAI.

Ask an observability tool when the next outage will occur, and you may get an answer. Ask it to automate a known failure mode, and it performs a perfect dance. Ask an observability tool if the enterprise is OK, and you get nothing. The question is beyond its capabilities. Observability tools as they exist today focus on IT, including developers in DevOps pipelines, operations management team members working to keep the lights on, and the newly coined (by my more than 40-year standard) system reliability engineers (SREs). Observability explains the data from monitoring.

Enter GenAI, the big rock in the pond creating its version of chaos. In chaos theory, a single element can tip an entire system over the edge. The math makes this abundantly clear (I’ll get to that in a moment). So, what happens next?

GenAI is already improving IT, from better chatbots to consuming all the data and providing remarkable insights. Yet GenAI is brand new and disruptive. Few observability vendors are using it to significant effect now, and a smaller number can predict the impacts in 24 to 26 months.

Observability can slow the devolution into chaos, pointing to a calmer IT environment with GenAI somewhere in the future. Actual intelligence for the enterprise comes when GenAI consumes data from every source in the company, allowing unthinkable questions and a future where the tsunami of GenAI-created change does not disrupt the company.

Chaos Theory: What Is It?

I’ve mentioned chaos theory a few times. Let’s look into what it is. Chaos theory is a popular trope that allows writers to invent seemingly impossible situations the protagonists must overcome or to base an entire story concept on moving a single item. If any large-scale, easily conceived system can be said to embody chaos, then information technology stands out. Chaos is the normal state of IT, particularly in large enterprises. I’m going to lay out the math for you.

Hold on. Why am I writing about mathematics in an IT blog?

I’m a physicist, and though I’ve been doing IT for over 40 years, I rely on my education for even the most mundane things. Observability and chaos theory are related—the how and why are essential when we look at the entire enterprise. I could have used entropy, but chaos theory is sexier and closer to the reality of an IT ecosystem. Now, to the esoteric math discussion.

Chaos theory has equations that help mathematicians and physicists analyze the systems under study. In 1975, Robert May created a model to demonstrate the chaotic behavior of dynamic systems. I have modified May’s model for incidents:

In+1 = r • In • (1 – In)

    • In
      • The proportion of the system’s capacity affected by incidents at a given time includes the number of incidents, severity, or the total impact on the system, with the value ranging from zero (no impact) to one (full impact or system-wide failure).
      • In a perfect world, this is always zero, but this is about IT, where the value is never zero. Oh, but we do try hard. NASA has some of the best methods and processes anywhere, but the first place they looked after the Challenger explosion was the range safety code, which can blow up the shuttle. It was deemed perfect after a multimillion-dollar, line-by-line examination.
    • r
      • This represents the rate of incident generation and resolution, influenced by factors such as system complexity, change frequency, and the effectiveness of incident management processes. High values indicate a system where incidents are rapidly generated or poorly resolved, leading to a more chaotic system. Lower values suggest a stable system where incidents are effectively managed or are infrequent.
      • In another perfect world, perhaps in the multiverse, this would be equal to or less than one. In this same universe, pigs fly, and nothing ever breaks. I’m sure other strange things happen in this utopia to take the shine off the whole perfection thing.

In another version of Earth, I can simulate every IT element to identify systems and processes on the precipice of chaos and magically heal them. IT does not create dinosaurs, except in the form of mainframe computers running COBOL.

OK, that isn’t happening, but I can monitor all those elements and gather state information (on or off), metrics (memory usage, CPU performance), and more. Then I can send all that information to a team to determine the system’s chaos level and respond accordingly.

Oops, BAM! We have another data glut (monitoring often accounts for 25% of network traffic in a large enterprise).

Observability strives to infer a system’s internal state from its external outputs. We have scads of data but no idea what it means. Observability tooling, whether specifically for public and private clouds, networks, storage, or applications, is a view into the chaos.

The Intersection of May’s Equation and Observability

May’s equation and observability intersect. Here’s how:

      • Understanding system behavior: Observability and May’s equation aim to enhance understanding of complex systems. Observability allows for real-time monitoring and knowledge of a system’s state based on outputs, while May’s equation shows how system behavior can change dramatically with slight parameter shifts.
      • Predictability and stability: May’s equation highlights the limits of predictability in complex systems due to their sensitivity to initial conditions. Observability, in contrast, is a tool for gaining insight into the system. It increases predictability by allowing for early detection of minor issues before they escalate into significant problems. Thus, the value of “r” above keeps our system from exploding into chaos.
      • Adapting to change: The logistic map in May’s equation shows how systems can transition from stable to chaotic regimes with a single parameter change. Observability provides the means to detect and respond to these transitions, offering a method to help manage and mitigate the risks of entering chaotic states.
      • Feedback loops: Observability can act as a feedback mechanism in complex IT systems, identifying when a system is approaching a chaotic regime. This feedback can inform adjustments to system parameters to maintain desired performance and stability levels.

Technology impacts us almost everywhere—doctor visits, the news, social media, refrigerators, and even our cars (including gas-powered vehicles). The change in a single parameter can bring a company to its knees. Ask AT&T about a simple configuration change that brought their entire network down. Look into how British Airways had to cancel hundreds of flights because a software component failed after a simple change.

IT systems are always on the precipice of chaos. Observability tools are one way to examine every IT enterprise’s chaotic state.

Next Steps

To learn more, take a look at GigaOm’s cloud observability Key Criteria and Radar reports. These reports provide a comprehensive overview of the market, outline the criteria you’ll want to consider in a purchase decision, and evaluate how a number of vendors perform against those decision criteria.

If you’re not yet a GigaOm subscriber, you can access the research using a free trial.

The post Chaos Theory and Observability appeared first on Gigaom.



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