Operations | Monitoring | ITSM | DevOps | Cloud

Today, I am excited to share that we secured $188M in a new funding round, at a valuation of $1.19B (read more here). At the outset, I want to thank our employees, partners, investors and most importantly, our customers for this important milestone. The funding follows a year of unmatched innovation that led to accelerated revenue growth, installed base growth, and rapid community adoption of our open source projects.

Site Reliability Engineering (SRE) and Operations teams responsible for operating virtual machines (VMs) are always looking for ways to provide a more stable, more scalable environment for their development partners. Part of providing that stable experience is having telemetry data (metrics, logs and traces) from systems and applications so you can monitor and troubleshoot effectively.

This is a basic introduction to Lambda triggers that uses DynamoDB as an event source example. We talk a lot about the more advanced level of Lambda triggers in our popular two-part series: Complete Guide to Lambda Triggers. If you want to learn more, read part one and part two. We’re going back to the basics this time because skipping some steps when learning something new might get you confused. It tends to get annoying, or it can even make you frustrated. Why?

Your modern cloud-hosted applications rely on a number of key components—such as databases and load balancers—that are managed by the cloud provider. While these cloud resources can reduce the overhead of maintaining your own infrastructure, capturing and contextualizing monitoring data from services you don’t own can be difficult.

For the people using Azure Service Bus namespaces – we often have the need to ensure the Azure Service Bus Performance by testing our system integration by generating some test messages on the Azure Service Bus resources. You might need this for QA/Development for performance testing, load testing etc. This blog will explain how to simulate the test environment using Serverless360 to check Azure Service Bus performance and its throughput.

As applications move from monolithic architectures to microservices-based architectures, DevOps and Site Reliability Engineering (SRE) teams face new operational challenges. Microservices are updated constantly with new features and resource managers/schedulers (like Kubernetes and GKE) can add/remove containers in response to changing workloads. The old way of creating alerts based on learned behaviors of your monolithic applications will not work with microservices applications.

Log management stopped being a very simple operation quite some time ago. Long gone are the “good old days” when you could log into the machine, check the logs, and grep for the interesting parts. Right now things are better. With the observability tools that are now a part of our everyday lives, we can easily troubleshoot without the need to connect to servers at all. With the right tools, we can even predict potential issues and be alerted at the same time an incident happens.

Though government agencies continue to move to the cloud to accelerate their digital transformation plans, the majority have embraced a hybrid IT environment. This mix of on-premises and cloud implementations highlights the need for comprehensive, full-stack visibility across the entire hybrid IT environment. Without a broad view, agencies may not be able to see their cloud environment as clearly as they see what’s in the data center.

Alibaba Cloud is an important partner to us here at Elastic. We officially started our collaboration and strategic partnership with Alibaba Cloud back in 2017, when we announced the Alibaba Cloud Elasticsearch service. Since then, we’ve seen rapid adoption and growth of the service, which now supports more than 10 petabytes of data.