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Part 3: Proving It Works
Parts 1 and 2 covered why this matters and how the runtime got healthy. But a healthy runtime isn't the same thing as a proven one. The only claim worth making to a test team is “your actual test suite will pass here,” and that took three separate checks, each one harder to fake than the last.
Check 1: Does the sandbox even work
Simplest possible test: a pod pinned to runtimeClassName: sysbox-runc, scheduled onto a labeled node.
apiVersion: v1

kind: Pod

metadata:

  name: sysbox-test

spec:

  runtimeClassName: sysbox-runc

  nodeSelector:

    sysbox-runtime: running

  containers:

    - name: test

      image: ubuntu:24.04

      command: ["/bin/bash", "-c", "cat /proc/self/uid_map; sleep 3600"]
A real user-namespace mapping, something like 0 100000 65536, confirms the pod is running in its own isolated UID range and not sharing the host's root. If this doesn't show up correctly, nothing past this point matters.
Check 2: Does nested Docker actually pull and run something
This one runs /sbin/init as the entrypoint, which is required so the nested, systemd-managed Docker daemon actually comes up inside the sandbox, with hostUsers: false and a Docker client config mounted in for the internal registry.
kubectl create secret generic docker-config-ar \

  --from-file=config.json=./docker-config.json \

  -n default
One thing bit us here that's worth calling out on its own. A placeholder credentials file (anything with a literal “{AUTH}” string still sitting in it) mounts into the pod just fine. No error. Looks correct. Then every single nested pull fails, and the failure message doesn't point back at the credential at all. The secret needs a real base64-encoded oauth2accesstoken entry, generated fresh, because Artifact Registry tokens are short-lived. That has to be part of whatever rotates credentials automatically, not something set once and forgotten. Second gotcha, smaller but just as annoying: pulling a public Docker Hub image through a virtual repository requires the /library/ segment for official images. docker-remote/hello-world fails. docker-remote/library/hello-world works. One path segment, and it cost real debugging time before anyone remembered the convention. Once both were right, a pull-and-run against the internal registry succeeded and printed the expected Docker Hub greeting. That's proof the nested daemon itself works, not just the sandbox around it.
Check 3: Does the library actually work, not just the daemon
This is the check that matters most and gets skipped most often. Nested Docker working doesn't mean Testcontainers works, because Testcontainers talks to Docker through its own bundled client, and that client can disagree with the daemon about API versions even when the daemon is completely fine. That's more or less exactly what happened: an older Testcontainers dependency threw client version 1.32 is too old. Minimum supported API version is 1.40, while the nested daemon was sitting there healthy on API 1.55. Nothing wrong with Sysbox, or with Docker. The client shipped inside the old Testcontainers jar just hadn't caught up. The fix was pinning the test application to a current Testcontainers release, 2.0.5, with a client that actually negotiates a modern API. The final proof was a small Java app, built into a fat jar with Maven, that pulls a base image through the internal repo, starts a container, runs a command inside it, and prints a marker on success:
docker run --rm \

  -v /var/run/docker.sock:/var/run/docker.sock \

  -v /root/.docker:/root/.docker:ro \

  -e DOCKER_CONFIG=/root/.docker \

  -e DOCKER_HOST=unix:///var/run/docker.sock \

  -e TESTCONTAINERS_RYUK_DISABLED=true \

  internal-docker-repo/testcontainers-java-smoke:latest
It connected, reported Server Version: 29.7.1 and API Version: 1.55, ran the command, and printed its own success marker with a clean exit code. That's the actual proof: not “the daemon runs,” but “a real Testcontainers workload runs.”
What's left
Functionally, this is done. Unprivileged pod, isolated nested daemon, authenticated pulls through internal repos only, a real Testcontainers run passing. What's left is cleanup: stripping temporary debug logging out of the patched binaries and re-running all three checks against the cleaned build before it ships into shared CI images.
Questions people actually ask
Does this need privileged: true? No, and that's really the whole point of using Sysbox instead of a DinD sidecar. Isolation comes from a real Linux user namespace, not from trusting the container not to misbehave. People also ask whether this works behind a fully air-gapped registry with no exceptions at all. It does, as long as the virtual repository actually mirrors what the test suite needs and the mounted credentials are current. The token failure above is the most common way this breaks in practice. A fair question: if nested Docker was working, why did Testcontainers still fail? Because the failure lived in the library's bundled client, not the runtime. Worth checking those two things separately rather than assuming a working daemon means a working test suite. One last question: is any of this GKE-specific? Some of it, yes. The Artifact Registry details and the node-labeling steps are GKE conventions. The runtime fixes themselves sit lower than that. They're about proc-filesystem handling and namespace passthrough, and they'd apply to any locked-down, no-egress Kubernetes environment regardless of which managed provider is running it. [table id=3 /] [post_title] => Part Three: Running Secure Docker-in-Docker on Locked-Down GKE [post_excerpt] => [post_status] => publish [comment_status] => closed [ping_status] => closed [post_password] => [post_name] => part-three-running-secure-docker-in-docker-on-locked-down-gke [to_ping] => [pinged] => [post_modified] => 2026-10-08 12:49:35 [post_modified_gmt] => 2026-10-08 12:49:35 [post_content_filtered] => [post_parent] => 0 [guid] => https://keyvatech.com/?p=5307 [menu_order] => 0 [post_type] => post [post_mime_type] => [comment_count] => 0 [filter] => raw ) [1] => WP_Post Object ( [ID] => 5305 [post_author] => 15 [post_date] => 2026-09-23 15:22:22 [post_date_gmt] => 2026-09-23 15:22:22 [post_content] =>
Part 2: Installing and Patching Sysbox for a Locked-Down Cluster
Part 1 covered why any of this is worth doing. This part is the actual runbook: what it took to get Sysbox running on a GKE cluster with no public internet access from any node or pod, reaching the outside world only through preconfigured virtual repositories in an internal Artifact Registry.
Step 1: Install the base runtime
Standard stuff, at least on paper. Sysbox ships as a privileged DaemonSet that runs once per labeled node. It mounts host paths like /etc, /run, /usr/bin, /usr/local/bin, /var/lib, and the systemd unit directories, then runs an installer script that lays down the Sysbox binaries, the systemd services, and a node label. RBAC is minimal: a ServiceAccount, a ClusterRole scoped to get and patch on nodes, a ClusterRoleBinding tying the two together.
kubectl label node <node-name> sysbox-install=yes

kubectl apply -f rbac/sysbox-rbac.yaml

kubectl apply -f runtime-class/sysbox-runtimeclass.yaml

kubectl apply -f daemonset/sysbox-deploy-k8s.yaml

Check it worked with:

systemctl status sysbox sysbox-mgr sysbox-fs

kubectl get runtimeclass sysbox-runc

kubectl get nodes -l sysbox-runtime=running
If all three services are active and the node carries the label, the base install is done. This part is genuinely easy. The rest of it isn't.
Step 2: Fix the installer for a node with no internet
Here's where the standard guidance stops applying. The stock installer script assumes it can reach the open internet to grab a few packages during setup. On a node with no outbound route at all, that assumption just doesn't hold, and it doesn't fail cleanly either. It hangs, or breaks somewhere unhelpful. The fix is a small overlay image. Rebase from an internal mirror of the installer image, add the one utility the deploy step actually needs (rsync, pulled through the internal registry rather than a public one), and swap in a patched installer script. The patched version stops assuming it can apt-install anything. Instead, it checks for the specific binaries Sysbox needs at runtime, fusermount3 and iptables, and fails immediately with a real error message if either is missing, instead of hanging while it tries to fetch them. It still runs the normal Sysbox checks around user-namespace procfs mounting and loading kernel modules like shiftfs when needed. This overlay approach isn't specific to Sysbox, either. Any DaemonSet installer that assumes internet access needs roughly this same treatment on a cluster that has none.
Step 3: The first real failure
Base install healthy, services up, label present. Then the first actual Sysbox pod failed on sandbox creation. The error traced back to the runtime's rootfs handling, specifically mounting binfmt_misc onto proc/sys/fs/binfmt_misc. It turned out the sandbox's root filesystem simply didn't have that proc path yet, and the default mkdir followed by mount logic had no fallback for it.
Step 4: Patch the runtime
This ended up touching two Sysbox components. In sysbox-runc, a dedicated procMount operation was added so binfmt_misc stops being handled like a normal rootfs mkdir followed by mount. Instead, the init helper remounts /proc, works from the namespace-aware /proc/1/root view, creates the destination there, and mounts it safely by file descriptor. Sysctl writes were also relaxed to tolerate a missing key, since some proc sysctl entries genuinely don't exist in this environment, and failing hard on that was pure noise. sysbox-fs needed a broader fix. A whole class of /proc/sys/* passthrough operations (lookup, open, read, write, readdir, readlink, setattr) were failing, and the real cause was that they weren't carrying enough process context into the namespace layer to correctly reproduce the caller's root, working directory, uid and gid, and capabilities. Once that context was attached, and the user namespace was deliberately stripped for generic proc-sys passthrough specifically, the permission and personality mismatches went away. A read-only filesystem edge case in temporary procfs mounting also needed a fallback instead of just failing outright. Both got rebuilt from source with multi-stage, multi-platform Dockerfiles, producing Linux amd64 binaries that replaced the host copies. Restart the services and it's done:
systemctl restart sysbox sysbox-mgr sysbox-fs

systemctl status sysbox sysbox-mgr sysbox-fs
With that in place, a basic Sysbox pod finally reached Running, and cat /proc/self/uid_map inside it showed a real user-namespace mapping. Small thing to check, but it's the tell that isolation is actually working and not just assumed. [table id=3 /] [post_title] => Part Two: Running Secure Docker-in-Docker on Locked-Down GKE [post_excerpt] => [post_status] => publish [comment_status] => closed [ping_status] => closed [post_password] => [post_name] => part-two-running-secure-docker-in-docker-on-locked-down-gke [to_ping] => [pinged] => [post_modified] => 2026-09-11 15:22:39 [post_modified_gmt] => 2026-09-11 15:22:39 [post_content_filtered] => [post_parent] => 0 [guid] => https://keyvatech.com/?p=5305 [menu_order] => 0 [post_type] => post [post_mime_type] => [comment_count] => 0 [filter] => raw ) [2] => WP_Post Object ( [ID] => 5303 [post_author] => 15 [post_date] => 2026-09-15 15:21:55 [post_date_gmt] => 2026-09-15 15:21:55 [post_content] => Notes on getting Sysbox working on a GKE cluster with zero public internet access, so Testcontainers based tests can run inside the same pipeline as everything else.
Part 1: Why It Matters
I've watched a handful of platform teams hit this same wall. They lock down GKE the way it's supposed to be locked down: no public egress from any node or pod, every dependency routed through a small set of preconfigured virtual repositories in Google Artifact Registry that cover Docker, npm, and Maven. Security signs off. Compliance signs off. Everyone moves on. Then the test team shows up and asks why their Testcontainers based integration suite won't run in the pipeline. Testcontainers is the default way teams run integration tests against real dependencies. Spin up a real Postgres. A real Kafka broker. Run the test against it. Tear it down when you're done. It's not a mock or an in-memory stand-in, which is exactly why it catches bugs that mocks hide. The problem is easy to state and annoying to actually solve: Testcontainers needs a real Docker daemon to talk to. On a laptop, that's nothing. Docker Desktop is right there. Inside a Kubernetes pod on a shared, locked-down cluster, it's a much harder question, because a pod isn't a VM. It shares a kernel with everything else scheduled on that node. Two answers usually come up, and neither one is good. First option: privileged: true, the Docker socket bind-mounted in from the host, maybe a full DinD sidecar running privileged. It works. It also gives a test container a fairly direct line to the host kernel, and if that container gets compromised or misbehaves, the blast radius isn't contained anymore. Most security teams won't approve this, and honestly, they're right not to. Second option: give up on running the tests in the pipeline at all. Push them to a separate, less locked-down environment, or worse, back onto individual developer laptops. That undoes the entire point. You're right back to “passed on my machine, failed in CI” - the exact failure mode integration testing exists to kill.
Where Sysbox actually helps
Sysbox is an open source runtime that sidesteps both bad options. A container running under Sysbox gets its own Docker daemon inside a real, isolated Linux user namespace. No --privileged flag, no host root access. The test container sees what looks like an ordinary Docker host, while the node just sees one more unprivileged pod, no different from anything else scheduled on it. That's the property that actually gets this past a security review. Not a promise that the workload will behave, but a real kernel-level boundary.
Why this is worth the engineering effort
The value case, stated plainly: get Sysbox working on a locked-down GKE cluster and test teams run real Testcontainers based integration tests inside the same CI/CD pipeline as everything else, on infrastructure security already trusts. No exception requests. No separate environments to manage. No convincing anyone to sign off on a privileged pod. There's a second benefit that's easy to overlook. Once the cluster has this capability, every team building test infrastructure just inherits it. Nobody has to go through the privileged container question team by team, project by project. The next two parts get into how this actually gets built on a cluster with no internet egress: two runtime bugs that only show up in that kind of environment, and the exact checks that prove a real Java Testcontainers run worked end to end. [table id=3 /] [post_title] => Part One: Running Secure Docker-in-Docker on Locked-Down GKE [post_excerpt] => [post_status] => publish [comment_status] => closed [ping_status] => closed [post_password] => [post_name] => part-one-running-secure-docker-in-docker-on-locked-down-gke [to_ping] => [pinged] => [post_modified] => 2026-09-11 15:22:10 [post_modified_gmt] => 2026-09-11 15:22:10 [post_content_filtered] => [post_parent] => 0 [guid] => https://keyvatech.com/?p=5303 [menu_order] => 0 [post_type] => post [post_mime_type] => [comment_count] => 0 [filter] => raw ) [3] => WP_Post Object ( [ID] => 5332 [post_author] => 15 [post_date] => 2026-09-10 14:07:20 [post_date_gmt] => 2026-09-10 14:07:20 [post_content] =>

Keyva is pleased to announce the certification of the Keyva BMC Atrium Data Pump for the new ServiceNow Australia release. Clients can now seamlessly upgrade their ServiceNow App from previous ServiceNow releases (Zurich, Yokohama, Xanadu) to the Australia release.

The ServiceNow Australia release delivers enhanced AI-driven workflows, improved user experiences, and expanded automation capabilities to increase productivity, resilience, and service efficiency across the enterprise.

Keyva's BMC Atrium Data Pump provides synchronization of CIs, CI attributes, and relationships from the ServiceNow CMDB into the BMC Atrium CMDB. This integration allows organizations to leverage their existing investment in Enterprise Software and avoid costly "Rip and Replace" projects.

Learn more about the Keyva BMC Atrium Data Pump and view all the ServiceNow releases for which Keyva has been certified at the ServiceNow Store: store.servicenow.com.

[post_title] => Keyva BMC Atrium Data Pump ServiceNow to BMC Certified for Australia Release [post_excerpt] => [post_status] => publish [comment_status] => closed [ping_status] => closed [post_password] => [post_name] => keyva-bmc-atrium-data-pump-servicenow-to-bmc-certified-for-australia-release [to_ping] => [pinged] => [post_modified] => 2026-09-03 14:11:01 [post_modified_gmt] => 2026-09-03 14:11:01 [post_content_filtered] => [post_parent] => 0 [guid] => https://keyvatech.com/?p=5332 [menu_order] => 0 [post_type] => post [post_mime_type] => [comment_count] => 0 [filter] => raw ) [4] => WP_Post Object ( [ID] => 5350 [post_author] => 15 [post_date] => 2026-09-09 16:29:47 [post_date_gmt] => 2026-09-09 16:29:47 [post_content] =>

Software has moved well beyond its back-office origins. For most organizations today, it's the product, the primary customer touchpoint, or the system determining whether an order ships on time. As the stakes attached to application decisions continue to rise, so does the cost of getting them wrong.

Many organizations face an additional challenge: managing an older platform that still carries essential business logic, one that current staff no longer fully understand. Whether you're building something new or carrying an existing system forward, application development is what determines whether software becomes a long-term business asset or an accumulating liability.

We design, build, and modernize applications for organizations that depend on their software to perform reliably under real business pressure. The starting point differs from one engagement to the next, but the underlying discipline does not.

Discovery and Understanding: Where the Real Work Begins

A significant share of application projects go wrong before a single line of code is written. The problem the system was meant to solve was never fully understood in the first place. Engagements begin with the people who will actually use and depend on the system, rather than a predetermined list of assumed features. Time invested in discovery reduces the risk of building the wrong thing quickly and having to rebuild it later at greater cost.

Architecture receives the same level of attention. Transaction volume, regulatory requirements, and the way a system needs to interact with everything around it all inform the technical approach. Rather than defaulting to whichever pattern happens to be familiar or currently popular, we design based on actual need. A payment platform and an internal reporting tool carry different demands, even when it would be simpler to design them the same way.

Modernizing Legacy Systems: The Hidden Knowledge Problem

Legacy systems tend to carry more institutional knowledge than they appear to on the surface. A platform that has been in production for fifteen or twenty years typically encodes a substantial number of business rules that were never formally documented. Many were established through past incidents the organization has no interest in repeating.

Before any component is replaced, we invest time in understanding what the code is actually doing. This is often a different question than what the existing documentation describes. Modernization that skips this step risks discarding logic that was quietly load-bearing. This gap tends to surface only after the new system is already in production.

This is one reason engagements are delivered in stages rather than as a single large cutover. A comprehensive rewrite delivered all at once depends on every assumption being correct from the outset. This is rarely the case in practice. Delivering in smaller, working increments allows the business to see progress along the way, identify issues while they remain inexpensive to correct, and adjust direction before significant effort has been committed to a flawed assumption.

Data migration follows the same principle. Data is mapped, validated, and reconciled as it moves between systems. A migration that is technically complete but has quietly introduced data integrity issues has not truly succeeded, even if it appears to have.

Critical Considerations Often Overlooked

Integration Design Matters from Day One

Very few applications operate in isolation. A system that cannot integrate cleanly with the environment around it tends to become disconnected within a relatively short period. This requires additional work later to reconnect it, typically under less favorable conditions than if the integration had been designed in from the outset.

Quality Assurance Isn't a Final Step

Testing is subject to similar pressure, often deprioritized as deadlines approach. Building quality assurance into the development process from the beginning allows issues to be identified while they remain inexpensive to resolve. It also gives teams the confidence to release changes at a sustainable pace.

Modern Infrastructure Requires Modern Architecture

When a legacy system moves to modern infrastructure, the objective extends beyond relocation. Re-architecting the system to take genuine advantage of what a modern, cloud-native platform provides is what allows the application to scale with the business. Without this consideration, it becomes a constraint on growth instead.

How We Approach Custom Application Development

Most organizations we work with already employ capable engineers. What is typically in shorter supply is sufficient capacity, whether measured in headcount or available time. These constraints make it difficult to take on a substantial build or modernization initiative without disrupting existing priorities. This is generally where our engagement begins: working alongside your existing team rather than in place of it.

Your engineers remain engaged for the duration of the project, well beyond the initial kickoff. Knowledge is transferred in both directions. By the conclusion of the engagement, your team should understand the system well enough to operate it, extend it, and explain it to future hires. Every engagement includes formal training and documentation to support that outcome. A system your organization does not fully understand becomes its own form of technical debt over time.

Scope, Security, and Sustainable Success

We maintain transparency around scope. In some cases, a full rebuild is genuinely the right answer. In many others, a smaller and more targeted solution addresses the underlying business need. Part of working responsibly means recommending that option even when a larger engagement would be more advantageous to us commercially.

Progress is evaluated against whether the actual business problem is being resolved. This happens through regular conversations with the people who will ultimately depend on the result. Rather than tracking solely through delivery metrics that can appear favorable right up until launch and prove otherwise afterward, we focus on outcomes that matter.

Security is treated as an integral part of development rather than a separate, later phase. Depending on the industry and the sensitivity of the data or transactions involved, this typically includes secure coding practices, access controls, and applicable compliance requirements addressed from the earliest stages of the project. The team responsible for planning the work is also the team that builds and supports it. Recommendations are grounded in prior delivery experience rather than theoretical best practice.

Application Development Across Industries

Our teams have delivered this kind of work in financial services, retail, industrial and agricultural operations, and healthcare. We've worked on systems ranging from customer-facing platforms processing significant transaction volume to internal tools that never reach an end customer directly. Regulatory requirements and tolerance for downtime vary meaningfully across these industries, but the underlying approach remains consistent.

If your organization is evaluating a new build, a modernization initiative, or simply needs additional capacity on something business-critical, we would welcome the conversation.

[table id=3 /]

[post_title] => Application Development and Software Modernization: Building Systems That Drive Business Results [post_excerpt] => [post_status] => publish [comment_status] => closed [ping_status] => closed [post_password] => [post_name] => application-development-and-software-modernization [to_ping] => [pinged] => [post_modified] => 2026-09-09 16:29:47 [post_modified_gmt] => 2026-09-09 16:29:47 [post_content_filtered] => [post_parent] => 0 [guid] => https://keyvatech.com/?p=5350 [menu_order] => 0 [post_type] => post [post_mime_type] => [comment_count] => 0 [filter] => raw ) [5] => WP_Post Object ( [ID] => 5327 [post_author] => 15 [post_date] => 2026-09-08 13:59:03 [post_date_gmt] => 2026-09-08 13:59:03 [post_content] =>

Keyva is pleased to announce the certification of the Keyva BMC Atrium Data Pump for the new ServiceNow Australia release. Clients can now seamlessly upgrade their ServiceNow App from previous ServiceNow releases (Zurich, Yokohama, Xanadu) to the Australia release.

The ServiceNow Australia release delivers enhanced AI-driven workflows, improved user experiences, and expanded automation capabilities to increase productivity, resilience, and service efficiency across the enterprise.

Keyva's BMC Atrium Data Pump provides synchronization of CIs, CI attributes, and relationships from the BMC Atrium CMDB into the ServiceNow CMDB. This integration allows organizations to leverage their existing investment in Enterprise Software and avoid costly "Rip and Replace" projects.

Learn more about the Keyva BMC Atrium Data Pump and view all the ServiceNow releases for which Keyva has been certified at the ServiceNow Store: store.servicenow.com.

[post_title] => Keyva BMC Atrium Data Pump BMC to ServiceNow Certified for Australia Release [post_excerpt] => [post_status] => publish [comment_status] => closed [ping_status] => closed [post_password] => [post_name] => keyva-bmc-atrium-data-pump-certified-for-australia-release [to_ping] => [pinged] => [post_modified] => 2026-09-03 14:10:51 [post_modified_gmt] => 2026-09-03 14:10:51 [post_content_filtered] => [post_parent] => 0 [guid] => https://keyvatech.com/?p=5327 [menu_order] => 0 [post_type] => post [post_mime_type] => [comment_count] => 0 [filter] => raw ) [6] => WP_Post Object ( [ID] => 5324 [post_author] => 15 [post_date] => 2026-09-04 13:57:23 [post_date_gmt] => 2026-09-04 13:57:23 [post_content] =>

Keyva is pleased to announce the certification of the Keyva HP Universal CMDB Data Pump for the new ServiceNow Australia release. Clients can now seamlessly upgrade their ServiceNow App from previous ServiceNow releases (Zurich, Yokohama, Xanadu) to the Australia release.

The ServiceNow Australia release delivers enhanced AI-driven workflows, improved user experiences, and expanded automation capabilities to increase productivity, resilience, and service efficiency across the enterprise.

Keyva's HP Universal CMDB Data Pump provides synchronization of CIs, CI attributes, and relationships from the ServiceNow CMDB into the HP Universal CMDB. This integration allows organizations to leverage their existing investment in Enterprise Software and avoid costly "Rip and Replace" projects.

Learn more about the Keyva HP Universal CMDB Data Pump and view all the ServiceNow releases for which Keyva has been certified at the ServiceNow Store: store.servicenow.com.

[post_title] => Keyva HP Universal CMDB Data Pump Certified for Australia Release [post_excerpt] => [post_status] => publish [comment_status] => closed [ping_status] => closed [post_password] => [post_name] => keyva-hp-universal-cmdb-data-pump-certified-for-australia-release [to_ping] => [pinged] => [post_modified] => 2026-09-03 14:10:37 [post_modified_gmt] => 2026-09-03 14:10:37 [post_content_filtered] => [post_parent] => 0 [guid] => https://keyvatech.com/?p=5324 [menu_order] => 0 [post_type] => post [post_mime_type] => [comment_count] => 0 [filter] => raw ) [7] => WP_Post Object ( [ID] => 5335 [post_author] => 15 [post_date] => 2026-09-03 14:09:35 [post_date_gmt] => 2026-09-03 14:09:35 [post_content] =>

Keyva is pleased to announce the certification of the Keyva VMware Orchestration for the new ServiceNow Australia release. Clients can now seamlessly upgrade their ServiceNow App from previous ServiceNow releases (Zurich, Yokohama, Xanadu) to the Australia release.

The ServiceNow Australia release delivers enhanced AI-driven workflows, improved user experiences, and expanded automation capabilities to increase productivity, resilience, and service efficiency across the enterprise.

Keyva's VMware Orchestration allows users to trigger VMware operations directly from ServiceNow Catalog Requests, Change Requests, Incident Requests, and more. Users have the flexibility to configure custom triggers and define specific conditions for launch, ensuring that any approvals established within ServiceNow are completed before the corresponding VMware operation is initiated. This integration allows organizations to fulfill infrastructure automation requests through VMware from a centralized ServiceNow service catalog, without requiring additional ServiceNow licensing.

Learn more about the Keyva VMware Orchestration and view all the ServiceNow releases for which Keyva has been certified at the ServiceNow Store: store.servicenow.com.

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Part 3: Proving It Works
Parts 1 and 2 covered why this matters and how the runtime got healthy. But a healthy runtime isn't the same thing as a proven one. The only claim worth making to a test team is “your actual test suite will pass here,” and that took three separate checks, each one harder to fake than the last.
Check 1: Does the sandbox even work
Simplest possible test: a pod pinned to runtimeClassName: sysbox-runc, scheduled onto a labeled node.
apiVersion: v1

kind: Pod

metadata:

  name: sysbox-test

spec:

  runtimeClassName: sysbox-runc

  nodeSelector:

    sysbox-runtime: running

  containers:

    - name: test

      image: ubuntu:24.04

      command: ["/bin/bash", "-c", "cat /proc/self/uid_map; sleep 3600"]
A real user-namespace mapping, something like 0 100000 65536, confirms the pod is running in its own isolated UID range and not sharing the host's root. If this doesn't show up correctly, nothing past this point matters.
Check 2: Does nested Docker actually pull and run something
This one runs /sbin/init as the entrypoint, which is required so the nested, systemd-managed Docker daemon actually comes up inside the sandbox, with hostUsers: false and a Docker client config mounted in for the internal registry.
kubectl create secret generic docker-config-ar \

  --from-file=config.json=./docker-config.json \

  -n default
One thing bit us here that's worth calling out on its own. A placeholder credentials file (anything with a literal “{AUTH}” string still sitting in it) mounts into the pod just fine. No error. Looks correct. Then every single nested pull fails, and the failure message doesn't point back at the credential at all. The secret needs a real base64-encoded oauth2accesstoken entry, generated fresh, because Artifact Registry tokens are short-lived. That has to be part of whatever rotates credentials automatically, not something set once and forgotten. Second gotcha, smaller but just as annoying: pulling a public Docker Hub image through a virtual repository requires the /library/ segment for official images. docker-remote/hello-world fails. docker-remote/library/hello-world works. One path segment, and it cost real debugging time before anyone remembered the convention. Once both were right, a pull-and-run against the internal registry succeeded and printed the expected Docker Hub greeting. That's proof the nested daemon itself works, not just the sandbox around it.
Check 3: Does the library actually work, not just the daemon
This is the check that matters most and gets skipped most often. Nested Docker working doesn't mean Testcontainers works, because Testcontainers talks to Docker through its own bundled client, and that client can disagree with the daemon about API versions even when the daemon is completely fine. That's more or less exactly what happened: an older Testcontainers dependency threw client version 1.32 is too old. Minimum supported API version is 1.40, while the nested daemon was sitting there healthy on API 1.55. Nothing wrong with Sysbox, or with Docker. The client shipped inside the old Testcontainers jar just hadn't caught up. The fix was pinning the test application to a current Testcontainers release, 2.0.5, with a client that actually negotiates a modern API. The final proof was a small Java app, built into a fat jar with Maven, that pulls a base image through the internal repo, starts a container, runs a command inside it, and prints a marker on success:
docker run --rm \

  -v /var/run/docker.sock:/var/run/docker.sock \

  -v /root/.docker:/root/.docker:ro \

  -e DOCKER_CONFIG=/root/.docker \

  -e DOCKER_HOST=unix:///var/run/docker.sock \

  -e TESTCONTAINERS_RYUK_DISABLED=true \

  internal-docker-repo/testcontainers-java-smoke:latest
It connected, reported Server Version: 29.7.1 and API Version: 1.55, ran the command, and printed its own success marker with a clean exit code. That's the actual proof: not “the daemon runs,” but “a real Testcontainers workload runs.”
What's left
Functionally, this is done. Unprivileged pod, isolated nested daemon, authenticated pulls through internal repos only, a real Testcontainers run passing. What's left is cleanup: stripping temporary debug logging out of the patched binaries and re-running all three checks against the cleaned build before it ships into shared CI images.
Questions people actually ask
Does this need privileged: true? No, and that's really the whole point of using Sysbox instead of a DinD sidecar. Isolation comes from a real Linux user namespace, not from trusting the container not to misbehave. People also ask whether this works behind a fully air-gapped registry with no exceptions at all. It does, as long as the virtual repository actually mirrors what the test suite needs and the mounted credentials are current. The token failure above is the most common way this breaks in practice. A fair question: if nested Docker was working, why did Testcontainers still fail? Because the failure lived in the library's bundled client, not the runtime. Worth checking those two things separately rather than assuming a working daemon means a working test suite. One last question: is any of this GKE-specific? Some of it, yes. The Artifact Registry details and the node-labeling steps are GKE conventions. The runtime fixes themselves sit lower than that. They're about proc-filesystem handling and namespace passthrough, and they'd apply to any locked-down, no-egress Kubernetes environment regardless of which managed provider is running it. [table id=3 /] [post_title] => Part Three: Running Secure Docker-in-Docker on Locked-Down GKE [post_excerpt] => [post_status] => publish [comment_status] => closed [ping_status] => closed [post_password] => [post_name] => part-three-running-secure-docker-in-docker-on-locked-down-gke [to_ping] => [pinged] => [post_modified] => 2026-10-08 12:49:35 [post_modified_gmt] => 2026-10-08 12:49:35 [post_content_filtered] => [post_parent] => 0 [guid] => https://keyvatech.com/?p=5307 [menu_order] => 0 [post_type] => post [post_mime_type] => [comment_count] => 0 [filter] => raw ) [comment_count] => 0 [current_comment] => -1 [found_posts] => 175 [max_num_pages] => 22 [max_num_comment_pages] => 0 [is_single] => [is_preview] => [is_page] => [is_archive] => [is_date] => [is_year] => [is_month] => [is_day] => [is_time] => [is_author] => [is_category] => [is_tag] => [is_tax] => [is_search] => [is_feed] => [is_comment_feed] => [is_trackback] => [is_home] => 1 [is_privacy_policy] => [is_404] => [is_embed] => [is_paged] => [is_admin] => [is_attachment] => [is_singular] => [is_robots] => [is_favicon] => [is_sitemap] => [is_posts_page] => [is_post_type_archive] => [query_vars_hash:WP_Query:private] => c0ac5b645bca5e8a351ed08806ccbf53 [query_vars_changed:WP_Query:private] => [thumbnails_cached] => [allow_query_attachment_by_filename:protected] => [stopwords:WP_Query:private] => [compat_fields:WP_Query:private] => Array ( [0] => query_vars_hash [1] => query_vars_changed ) [compat_methods:WP_Query:private] => Array ( [0] => init_query_flags [1] => parse_tax_query ) [query_cache_key:WP_Query:private] => wp_query:cb46a272b3f31498c88060117c9a6915 [tribe_is_event] => [tribe_is_multi_posttype] => [tribe_is_event_category] => [tribe_is_event_venue] => [tribe_is_event_organizer] => [tribe_is_event_query] => [tribe_is_past] => )

Part Three: Running Secure Docker-in-Docker on Locked-Down GKE

Part 3: Proving It Works Parts 1 and 2 covered why this matters and how the runtime got healthy. But a healthy runtime isn’t the same thing as a proven ...

Part Two: Running Secure Docker-in-Docker on Locked-Down GKE

Part 2: Installing and Patching Sysbox for a Locked-Down Cluster Part 1 covered why any of this is worth doing. This part is the actual runbook: what it took to ...

Part One: Running Secure Docker-in-Docker on Locked-Down GKE

Notes on getting Sysbox working on a GKE cluster with zero public internet access, so Testcontainers based tests can run inside the same pipeline as everything else. Part 1: Why ...

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