Operations | Monitoring | ITSM | DevOps | Cloud

While Instrumental offers broad support and integrations for application, server, service, and custom monitoring, certain AWS data is only available within the AWS CloudWatch service. Over the past few months, we’ve been testing a deep integration with CloudWatch and are excited to release it to all users. Like the rest of Instrumental, our CloudWatch integration is designed to be simple, configurable, and lightning-fast.

Exoprise recently released new storage sensors for end-to-end monitoring and testing of Azure Blob or Amazon S3. These sensors, once deployed against a container, enable continuous monitoring of access performance, uptime and availability of Azure Blob storage or Amazon S3. They enable network and storage administrators to test network capacity, latency and effective bandwidth to the various object store regions and datacenters that support the stores.

In this blogpost we will demonstrate how to build a complete GKE security stack for anomaly detection and to prevent container runtime security threats. We will integrate Falco runtime security engine with Google Cloud Functions and Pub/Sub.

Amazon ECS allows you to run Docker containers your application without having to actually manage physical hardware (or virtual hardware, in the case of the Fargate launch type). However, since it’s a managed service, you have less visibility with traditional monitoring tools. As such, it becomes even more important to take advantage of the available monitoring tools in AWS. In this post, we’ll explain how to use CloudWatch to monitor ECS and what is important to watch.

Following the recent announcement of our partnership with Microsoft, Azure users can now monitor, troubleshoot, and secure their environments with a fully managed Azure-native ELK solution. However, If you want to set up the ELK Stack on Azure on your own this guide will help you get started.

In the last post, Samuell (from the og-aws Slack group) figured out his negative TTL problems in Cloudfront. During that session, we actually solved two different problems. This post is to finish off that conversation and address the other problem, which was how to use the default error page in Cloudfront.

Welcome to the second edition of Serverless from the Trenches, our series of bite-sized blog posts aimed at developers and DevOps working in serverless. Each article will focus on a different technique or tool to solve a real-world problem and – hopefully – help make your work in serverless more productive. This week we look at how to add Cognito to your integration tests flow, making for true black box testing.

Just starting out with Dashbird? Great, you are in the right place. I’ve been speaking with hundreds of our new users in the past couple for months about their experience with Dashbird. I must say the feedback has been incredible so far. However, there are a few things I’ve noticed that our users haven’t yet taken advantage of within the platform. For a better success, let me point them out to you.

With the adoption of agile microservices, enterprise IT teams have rapidly transitioned from managing pets (physical and virtual servers) to cattle (public cloud services) to now chickens (containerized infrastructure). Container platforms like Docker and container orchestration engines like Kubernetes are helping IT operators drive greater agility, portability, and flexibility for scaling, managing, and optimizing microservices architectures.