If you’ve ever gotten sticker shock after receiving a surprisingly large cloud bill, this might have been your reaction… I think we’ve all been there. While the cloud makes flexible scaling possible, it has also introduced many new services one can use, resulting in increased cloud costs. In this article, I’ll go over the eight ways you can reduce your Kubernetes cloud costs. I use Amazon Web Services (AWS) as an example, but the lessons can also apply to other cloud providers.

In this tutorial, we will look into how to integrate performance testing in your development process with Google Cloud Build and k6. k6 is an open-source load testing tool for testing the performance of APIs, microservices, and websites. Developers use k6 to test a system's performance under a particular load to catch performance regressions or errors.

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.

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.

During the process of turning data into insights, the most compelling data often comes with an added responsibility—the need to protect the people whose lives are caught up in that data. Plenty of data sets include sensitive information, and it’s the duty of every organization, down to each individual, to ensure that sensitive information is handled appropriately.

Cloud testing is expected to grow to USD 11 Billion by 2023 , and we are talking about only cloud testing here, not cloud computing. Complex testing scenarios such as cross-browser testing, parallel testing, can be made more effective when done on the cloud. The reason being – the cloud provides the required testing environment effortlessly and can be scaled up or down as needed.

We have recently launched our disruptive Live Debugger on the Azure Marketplace, making it easier than ever before for teams on the Microsoft stack to slash the time they invest in debugging. We are excited about this, as we have been working closely with Microsoft to make sure that both large international enterprises as well as smaller and scaling startups have direct access to Rookout, to make the most out of our dynamic observability solutions.

Over the last year, perhaps unsurprisingly, increasing numbers of companies have made the jump to the cloud. It’s become a necessary move for so many businesses. But, as I discussed with Joe DosSantos on the latest episode of Data Brilliant – the rewards are abundant, but the journey is not always straight forward.

In this article, I'll walk you through the differences between self-hosted CI/CD and cloud-based CI/CD (like Bitrise!) and show you why it's time to move into the cloud.

The manufacturing industry, like any other industry, is not immune to data challenges. Sourcing data, wrangling it and ensuring it’s being used in a governed, standardized way are not uncommon problems. Particularly in manufacturing, issues surface with inventory management, within the supply chain and with logistics.

We just announced Cloudera DataFlow for the Public Cloud (CDF-PC), the first cloud-native runtime for Apache NiFi data flows. CDF-PC enables Apache NiFi users to run their existing data flows on a managed, auto-scaling platform with a streamlined way to deploy NiFi data flows and a central monitoring dashboard making it easier than ever before to operate NiFi data flows at scale in the public cloud.

Are you ready to turbo-charge your data flows on the cloud for maximum speed and efficiency? We are excited to announce the general availability of Cloudera DataFlow for the Public Cloud (CDF-PC) – a brand new experience on the Cloudera Data Platform (CDP) to address some of the key operational and monitoring challenges of standard Apache NiFi clusters that are overloaded with high-performant flows.

The best way to appreciate key concepts involving digital transformation is to look at real-world examples. In a recent Kong webinar, I sat down with Solutions Engineer Ahmed Koshok as he reviewed several real-world case studies that help illuminate the role of microservices in making digital transformation successful for organizations. The case studies included Papa John’s, NextJ Systems, and Yahoo! Japan.

Apps of today differ from those of the past. Evolving organizations like Cargill need to scale quickly to support millions of users, have global availability, manage petabytes or more of data and respond in milliseconds. That’s why modern apps now leverage API automation. ​​

Whether you're implementing a microservice architecture that will be scalable and resilient or forward-thinking for interoperability possibilities, APIs provide the essential level of abstraction that enables communication between separate pieces of software. Modifying an API architecture once it is live is no small feat, so taking the time before building one to identify your needs and goals for your API is a worthwhile step that will help you create the API you want.

Everyone knows that more and more data is moving to the cloud. According to the latest research, 94% of all enterprises use cloud services and 48% of businesses store classified and important data in the cloud. While the cloud is ubiquitous, in practice it consists of data infrastructures in various locations around the world. The question of where the cloud data infrastructure storing your specific data is located is becoming increasingly important.

A hands-on article about how to build and test your Android app on physical devices on the cloud with Espresso, AWS Device Farm, and Bitrise.

Amid the rapid pace of change felt by organizations this year, it’s no surprise that digital transformation projects have been high on the agenda for CIOs across the globe. To achieve both their organizational and transformation goals and become digitally agile as a result, CIOs are often tasked with creating the conditions needed to enable an intelligent and flexible digital core.

One of the core tasks during load testing is setting-up of required Test Agents or Load Generators. Though it is straightforward in most cases, it can be challenging and time-consuming when you do not have enough details required for hardware sizing and memory footprint and also need support for thousands of virtual users.

“40% of all enterprise workloads will be deployed in CIPS [cloud infrastructure and platform services] by 2023, up from only 20% in 2020.”.As the cloud permeates every aspect of business, decision-makers must make critical choices regarding infrastructure at every turn. Their answers will ultimately determine if every part of an organization is empowered to move forward in a cohesive way to reach business outcomes.

Joint customers can now stay within AWS for all cloud services and minimize data movement costs.

There are 3 critical differences between Bigtable and BigQuery.

What can we say: Research is non-linear, there are tests, and adjustments, and more tests, and more adjustments, and then we add more data, and test some more, and… you know the story.