Navigating Container Management Challenges: Strategies for Security, Integration, and Troubleshooting

Containers have transformed how software is built and deployed but they pose unique management challenges that can be daunting for DevOps teams to address. You need an effective strategy to mitigate security risks, integrate containers with legacy systems, and troubleshoot problems that affect your containerized apps and their host environments.

This article explains how to implement resilient container management techniques that solve these three verticals. We’ll explore best practices, real-world examples, and complementary tools that allow you to take control of your containers so you can operate them with confidence.

Container Security Risks and Mitigation Strategies

Correctly deployed containers can be more secure than traditional workloads. The container’s boundary isolates your apps from each other and their host. However, this protection is often weak by default and can be exploited by attackers. Problems such as running containers as root and incorrect use of Docker’s privileged mode erode available security protections, potentially enabling threats to escape containers.

It’s not just misconfigurations that can lead to issues—in the past few years, several vulnerabilities in container technologies and operating system kernels have been found to facilitate container escapes. DataDog reported that the Linux Dirty Pipe vulnerability can be used to break out of containers, for example, while the more recent “Leaky Vessels” bug in container runtime runc could be exploited to obtain access to the host’s filesystem.

Threats can also emerge from within containers via supply chain attacks. Malicious images and code dependencies are a relatively easy way to compromise your workflows and thwart detection. Research by JFrog published in April 2024 found that almost 20% of public image repositories on Docker Hub contain hostile content.

It’s not enough to “set and forget” containers and assume you’ll be protected. Defending against container security risks requires a comprehensive strategy that allows you to reliably detect threats, respond to them in real-time, and prevent them recurring.

There’s several ways to achieve this, starting with ensuring appropriate defenses are applied when images are built. Vet your base images for security threats and try to use smaller images that contain the minimum number of software packages and dependencies you require—this will reduce your attack surface. You can then use automated vulnerability scanners to detect known problems before they’re exposed, such as CVEs that exist within the container.

The second phase of container security happens at runtime. Containers should run with as few capabilities as possible, reducing the risk to your environment if an exploit does occur. It’s also important to adhere to the principle of least privilege by restricting user access to containers, minimizing the number of potential exploit pathways.

Learn the security controls available in your container platform and the best ways to combine them. Kubernetes is relatively simple to configure for a zero trust security architecture, for example, but this depends on you taking the time to enable features such as RBAC, network policies, and Pod security admission rules to enforce that security requirements are continually upheld. These are powerful mechanisms that can significantly enhance your protection, but they aren’t configured by default.

Integration Challenges with Legacy Systems

Wholesale migrations of legacy systems to containers are complex and not always viable, whether due to lack of resources, regulatory concerns, or a long-term intention to eventually launch a modern replacement. As a result, it’s common for containers to require integration with existing systems, but this often leads to its own challenges.

Containers typically reside in a different environment to legacy apps. Whereas older systems may be hosted on-premises and maintained using traditional deployment methods, containers will usually run in the cloud with high availability and scalability. Connecting the two together requires secure networking between the environments and correct service discovery so the systems can interact.

Integration efforts may be hampered by insufficient documentation and missing expertise for the legacy system. Older apps may also utilize outdated security standards or programming environments, which could expose the container environment to threats or prevent an easy integration from occurring.

You can make integration efforts run more smoothly by first cataloging your app inventory and its connectivity pathways. Once you’ve identified which aspects need to be maintained, you can develop new APIs and bridging layers that allow your containers to fetch required data from the legacy components, without requiring any direct interactions. Writing dedicated microservices that mediate with the legacy system allows you to remove the dependency upon it, keeping more of the processing within your modern container stack.

Companies that have successfully adopted this approach include PayPal, where containers have been used in conjunction with legacy apps since 2016. Because the firm’s technology was already well established, PayPal’s migration to containers inherently required a component of legacy integration. Its approach included a principle of staying “invisible” to developers, requiring no action on their part, and not fragmenting environments—once an app was containerized, it was launched into production to ensure the migration maintained its pace.

Insurance company MetLife saw similar success during its own migration to containers. It adopted a phased approach that kept the legacy apps active while they were gradually converted. New wrappers developed as microservices allowed different units of functionality to be reliably connected together, including the containerized and legacy environments.

These examples showcase how integration between containers and older systems is possible, provided you don’t expect a perfect one-size-fits-all solution on day one. Planning a methodical strategy, driven by the use of proper management tools that help you index your service inventory, allows you to effectively capitalize on containers today without cutting you off from essential legacy components.

Troubleshooting Dynamic Container Environments

It’s often said that containers make cloud operations simpler, but this doesn’t always seem the case when you’re getting started with container management at scale. Troubleshooting container environments is difficult because they’re so dynamic and ephemeral in nature; when containers are continually being replaced, it’s hard to obtain oversight of what’s running and where.

Container observability comprises several different facets, each of which contributes to the overall ease with which you can diagnose problems:

• Monitoring of metrics such as CPU consumption and Node utilization, enabling you to identify resource-related issues.
• Log aggregation and storage so you can investigate activity within your containerized apps, even after individual containers are destroyed.
• Detailed traces that allow you to pinpoint the causes of errors by viewing the events that led to them.

This data is best collected using dedicated tools like Prometheus, Grafana, and the Elastic Stack. They’re designed for cloud-native environments and have good support for container orchestrators such as Kubernetes, letting you automate key parts of the monitoring process.

Observability suites alone don’t always cut it though. Even when aided by these platforms, it can still be hard to understand how your inventory’s distributed across your cloud accounts and clusters. Centralized container management solutions such as Rafay and Rancher address this problem by offering a unified view of your resources, letting you apply actions to them in aggregate and more easily inspect inter-container communications.

Container troubleshooting is further simplified if you follow some basic best practices when you build and run your images. Containers should only ever host a single process, for example—starting more services in a container can cause errors that are difficult to debug, as you won’t be able to easily access their output.

Similarly, it’s important to architect your app’s main process so that it emits logs to its standard output and error streams (stdout/stderr). This ensures the information will be accessible to log aggregators. If your apps write logs to the container’s filesystem, then they won’t be automatically collected and could be lost if the container is stopped.

A final vital step is to ensure your app exposes its health state. Container management software needs to know if your app is performing as expected in order to raise the alarm about incidents and maintain high availability. Including health check instructions in your Dockerfiles lets you specify a command or HTTP endpoint that should be periodically checked for liveness; if the test doesn’t succeed, then tools like Kubernetes will automatically mark the container as failed and schedule a replacement. Not only does this help you detect when container failures occur, it also makes your app more reliable for users.

Enhancing Container Management with Complementary Technologies

You don’t have to manage your containers on your own. The ecosystem is stocked with tools, technologies, and platforms that simplify container management tasks, enabling you to achieve key use cases such as high availability, load balancing, central configuration, orchestration, and cost control.

Kubernetes is a popular way to operate containers in production. It automates the process of deploying and scaling your containers in distributed environments. Although Kubernetes is trailed by a reputation for complexity, fully managed services such as Amazon EKS and Google GKE make it possible to start new cloud clusters in seconds. These options also benefit from direct integration with the networking and security layers included in their respective cloud platforms.

Even simpler solutions are available for hands-off container management. Red Hat’s OpenShift allows you to easily build and run containers on Kubernetes without having to administer the underlying cluster, while enterprise Platform-as-a-Service (PaaS) solutions such as Rafay can do the same and fully automate tasks including app deployment, multi-tenant environments, and safe self-service developer access to your cluster and container fleets.

If you need to host your own infrastructure, then it’s best to utilize an Infrastructure-as-Code (IaC) approach. Tools such as Terraform and Ansible allow you to provision infrastructure resources including compute nodes and Kubernetes clusters from simple config files that you can store in a Git repository. This guarantees consistency, repeatability, and a clear audit trail of the changes that you make.

Because security is such a critical part of container operations, scan tools such as Anchore, Snyk, and Trivy should be regularly used to identify potential vulnerabilities and misconfigurations in your containers and their environments. These options generally work at the per-container level, but cloud-native app protection platforms (CNAPPs) like CrowdStrike and Wiz can be used to extend protection right across your infrastructure.

Utilizing a CNAPP for your container deployments provides end-to-end visibility of threats spanning cloud resources, workloads, runtime risks, and access management issues. This offers clear high-level visibility with the option of drilling down to precise details that allow threat connections to be discovered. The additional context helps facilitate more timely and effective security incident responses.

Container Management and Cloud Operations with Rafay

Containers simplify software development and help you realize the benefits of cloud deployment. Yet they also come with their own gotchas and pain points that can frustrate management initiatives. It’s vital to implement coherent strategies to address security risks, tightly integrate containers with legacy systems, and enable robust observability that permits accurate troubleshooting.

Platform-as-a-Service (PaaS) solutions are the best way to operate your containers without having to get hands-on with management. The Rafay enterprise PaaS unifies container environments across clouds, data centers, and edge workloads by joining your Kubernetes clusters into a single architecture. You can see all your containers in one place, letting you centrally manage resource utilization, governance policies, and developer identities.

With a range of flexible support options to match your needs—from fully managed through to self-hosted—Rafay is purpose-built for as-a-service container deployment. Start for free with Rafay to accelerate your container operations in the cloud, or check out our whitepaper on the essential requirements for enterprise Kubernetes management.