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Google has announced the general availability of its Stackdriver Cloud Monitoring dashboards API. The dashboards API is part of Google Cloud. It allows users to read the configuration for existing dashboards, create new dashboards, update existing dashboards and delete dashboards no longer used.
This article is a quick how-to after struggling with Google Cloud Build about how to send notifications when a build has failed or is successful. Since I did not want to use Slack and the heavy client, I give a try in this post with Telegram and discover the magical chatbot world.
You may also like: Serverless Is the New Build Server: Google CloudBuild (Container Builder) via NodeJS
Kubernetes is an open-source container orchestrator built by Google that helps run, manage, and scale containerized applications on the cloud. All the major cloud providers (Google Cloud, AWS, Azure, etc.) have managed Kubernetes platforms. In this article, we will discuss how to deploy a Spring Boot-based microservice with Google Cloud and undertake performance testing.
I first heard the term "data orchestration" earlier this year at a technical meetup in the San Francisco Bay Area. The presenter was Bin Fan, founding engineer and PMC maintainer of the Alluxio open source project.
Bin explained that data orchestration is a relatively new term. A data orchestration platform, he said, "brings your data closer to compute across clusters, regions, clouds, and countries."
The 2019 Accelerate State of DevOps report was published last week. This report is produced by DevOps Research and Assessment (DORA) team, which recently joined Google Cloud. They have collected data for over 6 years and surveyed over 31,000 professionals to gain insight into industry practices and associated business outcomes.
You may also enjoy: The State of DevOps
This is such an exciting report for us to read-not just because our product serves DevOps engineers, but because we ourselves are DevOps practitioners and love to see the detailed research and how we compare to our peers. There's a lot to process in this report, but here are some of the things we found most interesting.
It wouldn’t be wrong to state that the cloud computing arena has evolved beyond human contemplation over the past decade with companies usually at loggerheads when it comes to putting forth the first piece of technological innovation. Be it making development tools available for the users or increasing the efficacy of cognitive functions and machine learning principles, PaaS or Platform-as-a-Service has taken center-stage in this cloud-driven market. That said, at present, the competition has settled between Microsoft Azure, Google Cloud, IBM Cloud, and AWS, in regard to Enterprise-level cloud computing and other relatable strategies pertaining to digital transformation.
While AWS keeps leading the market with pioneered innovations, Microsoft has caught up courtesy of its pivotal role in the development of enterprise computing and IaaS offerings with the 365 Suite helping clients manage workloads with ease. IBM has also made a name for itself with a rich vein of security services, leaving Google anxious for necessary changes.
There are a lot of benefits to be gained from containerization if you haven’t already made the progression yet. Development teams can move at a much faster pace with containers running microservices. The transition from on-premise development servers to cloud environments is more seamless thanks to platforms like Kubernetes. As well as K8s, we also have robust cloud computing solutions like Google Cloud, Microsoft Azure, and Amazon Web Services natively supporting containers.
Moving from virtual machines to containers is a logical step in today’s modern software development world—especially given the fact that recent trends are geared towards application architecture being microservice-oriented. If you want to modernize your apps and take them to the next level, making the switch to a container-based environment is the first thing to do. There are multiple approaches to choose from and different ways to move from VMs to containers; we are going to discuss them in this article.
Ready to transition from a commercial database to open source, and want to know which databases are most popular in 2019? Wondering whether an on-premise vs. public cloud vs. hybrid cloud infrastructure is best for your database strategy? Or, considering adding a new database to your application and want to see which combinations are most popular? We found all the answers you need at the Percona Live event last month, and broke down the insights into the following free trends reports:
So, which databases are most popular in 2019? We broke down the data by open source databases vs. commercial databases:
You have surely read about Google Cloud (i.e. BigQuery, Dataproc), Amazon Redshift Spectrum, and Amazon Athena. Now, you are looking to take advantage of one or two. However, before you jump into the deep end, you will want to familiarize yourself with the opportunities of leveraging Apache Parquet instead of regular text, CSV, or TSV files. If you are not thinking about how to optimize for these new query service models, you are throwing money out the window.
Apache Parquet is a columnar storage format with the following characteristics:
In this post, we will explore how we can use Google Cloud Platform’s (GCP) Pub/Sub service in combination with a Spring Boot application using Spring Integration. We will send a message to a sender application which publishes the message to a Topic where a receiver application receives the messages of a Subscription.
GCP Pub/Sub is basically just like any other messaging system. You can send a message to a Topic where it is persisted, then a subscriber consumes the message, and after acknowledgment, the message is removed.
Google Cloud Platform security features cover a range of Google’s products and services, such as the popular G Suite applications. These products and services are built on one of the most secure data infrastructures in the world. But, it’s still your responsibility to make sure your Google apps security settings are set up properly. This is where these five Google Cloud security best practices come in handy.
When you first log in to your Google Admin console, everything will be grouped into a single organizational unit. Any settings you apply to this group will apply to all the users and devices in the organization. Planning out how you want to organize your organizational units and hierarchy before diving in will help you save time and create a more structured security strategy.
Google's Cloud Healthcare API is now available in beta. The API is meant to act as a bridge between on-site healthcare systems and applications hosted on Google Cloud. The goal of the API is to give hospitals and other healthcare facilities more analytical power and, in the long term, help them bring new healthcare solutions to the market.
The democratizing nature of DevOps has seen the responsibility of building and managing CI/CD pipelines transition from specialized release engineers to developers. But automating a robust, dependable CI/CD pipeline is tedious work. Developers need to connect to multiple tools to deliver software, and writing pipeline integrations for these services is a manual, error-prone process. There's research involved to ensure dependencies are accounted for, as well as debugging and maintaining integrations when updates are made. It's no wonder many teams put automating CI/CD firmly in the "too hard" basket.
Bitbucket Pipelines is a CI/CD tool in the cloud that's part of your repository and makes it easy for developers to configure pipelines with code. We are launching Bitbucket Pipes to make it easier to build powerful, automated CI/CD workflows in a plug-and-play fashion without the hassle of managing integrations. We've worked with industry leaders including Microsoft, AWS, Slack, Google Cloud, and more to build supported pipes that help automate your CI/CD pipeline, and made it simple to create your own to help abstract any duplicated configuration across your repositories.
According to the RightScale 2018 State of the Cloud report, serverless architecture penetration rate increased to 75 percent. Aware of what serverless means, you probably know that the market of cloudless architecture providers is no longer limited to major vendors such as AWS Lambda or Azure Functions. Now we have a range of cloud providers to choose from. But, why would anybody switch to serverless architecture? And what is the difference between all those providers and services they offer?
To answer that question, let’s roll back a bit. Fourteen years ago, cloud technologies began being adopted in IT. The market had to change rapidly, as every year brought new approaches to app development. First, businesses mostly utilized the IaaS (Infrastructure-as-a-Service) approach. It entailed renting servers and moving the infrastructure to clouds, but teams still had to deal with server setup. Then came the gradual dismissal of manual server operation, and PaaS (Platform-as-a-Service) appeared. PaaS providers offered a more complete application stack, like operating systems and databases to run in the cloud and be managed by the vendor. But that wasn’t enough.
This week all the major cloud vendors get lots of new functionality, so I'm providing my shortlist below.
AWS saw the introduction of AWS Solutions, the new catalog of reference architectures, and implementation templates.
In the CI/CD process, it is very common to use a Mule Maven plugin to build and deploy an application to the Cloudhub, on-premise private cloud like AWS, Azure, Google Cloud, etc. Since Mule 4, a lot of changes related to the deployment has changed, particularly related to the Mule Runtime Fabric (RTF). Actually, RTF is a completely new infrastructure for Mule application deployment. I will cover more on that topic later. In this article, I am going to cover the following topics related to the deployment to Anypoint Runtime Fabric (RTF):
If everything works, at the end, we should be able to achieve the following goals: