Operations | Monitoring | ITSM | DevOps | Cloud

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.

We’ve seen quite a bit of change this year as businesses have had to pivot to accelerating their digital transformation strategy, and placing even more emphasis on leveraging technology as a competitive differentiator. Most have continued to stress the importance of maintaining excellent customer relationships through their contact centers, but the playing field has changed as they now have to tap into data for insights that may have normally been gleaned through an analog approach.

Cloud Profiler is a favorite of Google Cloud customers thanks to the insight that it provides into the performance of your production code. You can use this knowledge to reduce and shorten outages, improve performance, and optimize compute spend—always a popular topic! Profiler has always provided the ability to view and compare CPU and memory performance over time through time filters and the comparison feature.

As Microsoft is forever releasing new functionality within Azure and all its offerings its often hard to keep abreast of the latest changes in technology. To do so, we here at SmiKar Software often follow influential and knowledgeable people that are experts in the their fields, to keep up to date ourselves. In no particular order, here are some of the noteworthy Azure Blogs that we follow.

AWS DynamoDB changed the database game in Serverless and continues to do so, as its design repeatedly proves its huge value. This guide takes you through everything there is to know about DynamoDB so you can rest assured you’re using the service in its best way and reaping all of the benefits.

Google Cloud has been gaining some noticeable traction in recent months: 43% growth in Q2 is nothing to sniff about, especially during a global recession. Masaf Dawood is director of Google Cloud services with SpringML, a premier Google Cloud partner with specialties in application development, data analytics, machine learning and marketing analytics. SpringML works exclusively with Google Cloud and has worked on 200 engagements with Google since the consultancy was founded in 2015.

If you’ve deployed an application or service to the Amazon Web Service (AWS) cloud, you’ve probably made use of an EC2 instance. One of the decisions that you had to make before you could start a new instance, was which instance type to use. Choosing an EC2 instance type can be a complicated process. AWS organizes their instance types into instance families, and within an instance family, there are varying sizes from micro to 32xlarge.

Deploying a stack into AWS is at the core of what Stackery helps you do. So much so that Stackery users deployed over 10,000 times last month! For the most part, this has been a manually executed process in our Web UI or command-line client. As teams grow and take on more work, fast and consistent deployments are key to scaling effectively. That’s why we’ve been working this year on continuous integration and deployment (CI/CD) features, tailor-built for serverless applications.

Today, AWS launched Amazon Timestream, a fast, scalable, serverless time series database purpose-built for IoT use cases. If you’re looking into trying out Timestream, know that you can visualize the native Timestream queries with Grafana out of the box. Here are some examples of the robust, SQL-style Timestream queries visualized in Grafana.