Operations | Monitoring | ITSM | DevOps | Cloud

The latest News and Information on Containers, Kubernetes, Docker and related technologies.

Securing AWS Fargate workloads: Meeting File Integrity Monitoring (FIM) requirements

Securing AWS Fargate serverless workloads can be tricky as AWS does not provide much detail about the internal workings. After all… it’s not your business, AWS manages the scaling of underlying resources for you. :) While the security and stability of Fargate’s system is an inherent feature, Fargate follows a shared responsibility model, where you still have to take care of securing those parts specific to your application..

Secure container orchestration at the edge

The cloud-native way of building software allows for consistency across developer environments and massive scalability of application deployments. Both these attributes are useful for edge, but create new challenges related to security and resilience. Watch this demo to see how Canonical’s modular technology stack addresses these challenges by using well-known cloud primitives.

AWS Fargate runtime security - Implementing File Integrity Monitoring with Sysdig

Thanks to serverless you can focus on your apps, instead of your infrastructure. Take AWS Fargate as an example. A service where you can deploy containers as Tasks, without worrying what physical machine they run on. However, without access to the host How can you detect suspicious activity? Like, file changes on your Fargate tasks? Sysdig provides runtime detection and response to secure Fargate serverless containers.

Datadog Live Containers - Kubernetes Resources

Datadog Live Containers provides multidimensional, real-time visibility into Kubernetes workloads, from Deployments and ReplicaSets down to individual Containers. Using Datadog's curated metrics, teams can track the health and performance of their Kubernetes resources in the appropriate context and surface critical information about every layer of their Cluster.

Dynamic Service Graph | Tigera - Long

Downtime is expensive and applications are a challenge to troubleshoot across a dynamic, distributed environment consisting of Kubernetes clusters. While development teams and service owners typically understand the microservices they are deploying, it’s often difficult to get a complete, shared view of dependencies and how all the services are communicating with each other across a cluster. Limited observability makes it extremely difficult to troubleshoot end-to-end connectivity issues which can impact application deployment.

Application Layer Observability | Tigera - Long

The majority of operational problems inherent to deploying microservices in a distributed architecture are linked to two areas: networking and observability. At the application layer (Layer 7), the need to understand all aspects associated with service-to-service communication within the cluster becomes paramount. Service-to-service network traffic at this layer is often using HTTP. DevOps teams struggle with these questions: Where is monitoring needed? How can I understand the impact of issues and effectively troubleshoot? And how can I effectively protect application-layer data?

DNS Dashboard | Tigera - Long

While it’s an essential part of Kubernetes, DNS is also a common source of outages and issues in Kubernetes clusters. Debugging and troubleshooting DNS issues in Kubernetes environments is not a trivial task given the limited amount of information Kubernetes provides for DNS queries. The DNS Dashboard in Calico Enterprise and Calico CLoud helps Kubernetes teams more quickly confirm or eliminate DNS as the root cause for microservice and application connectivity issues.

Kubernetes: Weighing Advantages and Disadvantages

Kubernetes is one of the current leading technologies. Its adoption has seen tremendous growth in the past few years. The concept of containers is a paradigm that appears to be the predominant medium of software development and deployment in the coming future. Containers help maintain consistency across various platforms, as they pack an application with its dependencies to help move it from one platform to another.

Guide to using Docker for your CI/CD pipelines

Docker is a platform for developers and sysadmins to develop, deploy, and run applications using containers. Docker is also referred to as an application packaging tool. This means that enabled applications can be configured and packaged into a Docker image that can be used to spawn Docker containers that run instances of the application. It provides many benefits including runtime environment isolation, consistency via code, and portability.

Keeping Watch Over Microservices and Containers

Splunk Director of Product Management Craig Hyde joins theCube’s John Furrier for a conversation in the Leading With Observability series. They discuss the importance of digital experience monitoring, especially as the world sees a boom in remote, online business and increasingly complex technological infrastructures. Why starting with the end user in mind is critical for setting observability goals How full-fidelity end-end tracing impacts troubleshooting, to detect and alert in seconds