System and application logs provide crucial data for operators and developers to troubleshoot and keep applications healthy. Google Cloud automatically captures log data for its services and makes it available in Cloud Logging and Cloud Monitoring. As you add more services to your fleet, tasks such as determining a budget for storing logs data and performing granular cross-project analysis can become challenging.
Running and troubleshooting production services requires deep visibility into your applications and infrastructure. Virtual machines running on Google Compute Engine (GCE) provide some system logs and metrics without any configuration required, but capturing application and advanced system data has required the installation of both a metrics agent and a logging agent.
Troubleshooting an application running on Google Kubernetes Engine (GKE) often means poking around various tools to find the key bit of information in your logs that leads to the root cause. With Cloud Operations, our integrated management suite, we’re working hard to provide the information that you need right where and when you need it. Today, we’re bringing GKE logs closer to where you are—in the Cloud Console—with a new logs tab in your GKE resource details pages.
Cloud Monitoring is one of the easiest ways you can gain visibility into the performance, availability, and health of your applications and infrastructure. Today, we’re excited to announce the lifting of three limits within Cloud Monitoring. First, the maximum number of projects that you can view together is now 375 (up from 100). Customers with 375 or fewer projects can view all their metrics at once, by putting all their projects within a single workspace.
Applications fail. Containers crash. It’s a fact of life that SRE and DevOps teams know all too well. To help navigate life’s hiccups, we’ve previously shared how to debug applications running on Google Kubernetes Engine (GKE). We’ve also updated the GKE dashboard with new easier-to-use troubleshooting flows. Today, we go one step further and show you how you can use these flows to quickly find and resolve issues in your applications and infrastructure.
People sometimes think that implementing Site Reliability Engineering (or DevOps for that matter) will magically make everything better. Just sprinkle a little bit of SRE fairy dust on your organization and your services will be more reliable, more profitable, and your IT, product and engineering teams will be happy. It’s easy to see why people think this way. Some of the world’s most reliable and scalable services run with the help of an SRE team, Google being the prime example.
A data center migration into the cloud is often a daunting business initiative that can take years as you transition your existing hardware, software, networking, and operations into a brand new environment. In our roles with Google Cloud’s Professional Services organization, we work side by side with customers to collaboratively architect and enable data center migrations into Google Cloud. Over the years, we’ve participated in multiple migration journeys, and devised a general approach.
Driving productivity of software development and delivery teams is critical for any organization. The six years of research by DevOps Research and Assessment (DORA) showcases the role easy-to-use tooling plays in driving this productivity and in turn a better work/life balance for the team. The research finds that highest performing teams are 1.5x more likely to have tools they consider easy to use.
