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.
One important aspect of managing a cloud environment is setting up financial governance to safeguard against budget overruns. Fortunately, Google Cloud lets you set quotas for a variety of services, which can play a key role in establishing guardrails—and protect against unforeseen cost spikes. And to help you set and manage quotas programmatically, we’re pleased to announce that the Service Usage API now supports quota limits in Preview.
At Google Cloud, we strive to bring Site Reliability Engineering (SRE) culture to our customers not only through training on organizational best practices, but also with the tools you need to run successful cloud services. Part and parcel of that is comprehensive observability tooling—logging, monitoring, tracing, profiling and debugging—which can help you troubleshoot production issues faster, increase release velocity and improve service reliability.
Do you have an application that’s a little… sluggish? Cloud Profiler, Google Cloud’s continuous application profiling tool, can quickly find poor performing code that slows your app performance and drives up your compute bill. In fact, by helping you find the source of memory leaks and other errors, Profiler has helped some of Google Cloud’s largest accounts reduce their CPU consumption by double-digit percentage points.
With more and more businesses moving online, and homegrown entrepreneurs spinning up new online apps, they’re increasingly looking for an online development platform to help them easily build and deploy their sites.
When you’re troubleshooting an app or a deployment, every second counts! Cloud Logging helps you troubleshoot by aggregating logs from across Google Cloud, on-premises or other clouds, indexing, aggregating logs into metrics, scanning for unique errors with Error Reporting and making logs available for search, all in less than a minute. And now, we’ve built two new features for streaming logs to give you even fresher insights from your logs data.
Developers and operators on IT and development teams want powerful metric querying, analysis, charting, and alerting capabilities to troubleshoot outages, perform root cause analysis, create custom SLI / SLOs, reports and analytics, set up complex alert logic, and more. So today we’re excited to announce the General Availability of Monitoring Query Language (MQL) in Cloud Monitoring! MQL represents a decade of learnings and improvements on Google’s internal metric query language.
Having good observability is vital to the health of your cloud infrastructure and applications, and a key element to using that information effectively is being able to create dashboards with relevant metrics. Today we are announcing a new dashboard creation experience from Cloud Monitoring that allows you to generate a greater variety of visualization types, introduces better flexibility for dashboard layouts, and makes data manipulation easier so you can create dashboards that better fit your needs.
The events of 2020 have accelerated ecommerce, increasing demand for and traffic on online marketplaces. Analyst eMarketer predicts that ecommerce sales in the United States will grow 18% in 2020, against an overall fall in total retail sales of 10.5% for the year. Likewise, our business—Japan-headquartered consumer-to-consumer marketplace Mercari Inc—is growing rapidly. In the United States alone, we have seen 74% year-on-year growth in monthly average users to 3.4 million.
Many organizations aspire to become true, high-functioning DevOps shops, but it can be hard to know where you stand. According to DevOps Research and Assessment, or DORA, you can prioritize just four metrics to measure the effectiveness of your DevOps organization—two to measure speed, and two to measure stability.
