We’re sure you’ve heard your DevOps team often talk about test orchestration. This testing approach has quickly become a crucial element of test automation because it streamlines the automation process. For agile teams, applying test orchestration to their testing strategy is quite rewarding as it accelerates testing and offers a holistic view of the testing process.

If you’ve done any reading about service meshes, you’ve probably come across mentions of an open source project named Envoy. And if you’ve done any reading about Envoy, you’ve probably seen references to service meshes. How are these two technologies related? How are they different? Do they work together? I’ll attempt to answer all those questions in this blog post’s first and second parts, plus possibly a few more.

We are happy to announce a new major release of Kuma, and a new major release of Kong Mesh built on Kuma! Kuma 1.3 ships with 10+ new features and countless improvements. Kong Mesh ships we enterprise capabilities for large scale service mesh deployments. We strongly suggest to upgrade, in order to take advantage of the latest and greatest when it comes to service mesh.

Earlier this year, Perforce hosted the Embedded DevOps Summit, exploring solutions to modern challenges in the planning, development, and testing stages of embedded software. As part of this event, Warren Savage, Visiting Researcher at the Applied Research Laboratory for Intelligence and Security (ARLIS) at the University of Maryland, presented Secure Collaboration in Cloud-Based Chip Design Environments.

French multinational automotive manufacturer Renault Group has been investing in Industry 4.0 since the early days. A primary objective of this transformation has been to leverage manufacturing and industrial equipment data through a robust and scalable platform. Renault designed an industrial data acquisition layer and connected it to Google Cloud, using optimized big data products and services that together form Renault's Industrial Data Platform.

Last week, we shared information on BigQuery APIs and how to use them, along with another blog on workload management best practices. This blog focuses on effectively monitoring BigQuery usage and related metrics to operationalize workload management we discussed so far.

Troubleshooting cloud services and infrastructure is an ongoing challenge for organizations of all sizes. As organizations adopt more cloud services and their cloud environments grow more complex, they naturally produce more telemetry data – including application, system and security logs that document all types of events. All cloud services and infrastructure components generate their own, distinct logs.

Modern business requires a range of digital components to communicate effectively when transferring data and delivering critical messages. Application programming interfaces, or APIs, are sets of rules that regulate exactly how certain apps or machines connect. If you work with data at all, you’ll have heard of REST or RESTful, and REST APIs — but what is REST API design? We explain below.

According to Forbes , 95% of companies need to manage unstructured data and use it to gain actionable insights. Data processing is the way to do just that. Unfortunately, poor data management occurs when companies don't make full use of the information they collect.

Apache Ozone is a scalable distributed object store that can efficiently manage billions of small and large files. Ozone natively provides Amazon S3 and Hadoop Filesystem compatible endpoints in addition to its own native object store API endpoint and is designed to work seamlessly with enterprise scale data warehousing, machine learning and streaming workloads. The object store is readily available alongside HDFS in CDP (Cloudera Data Platform) Private Cloud Base 7.1.3+.