Microservices are the future of software development. This approach serves as a server-side solution to development where services remain connected but work independently from each other. More developers are using microservices to improve performance, precision, and productivity, and analytical tools provide them with valuable insights about performance and service levels.
A microservices architecture creates an application as a collection of services. Each microservice works independently and uses application programming interfaces (APIs) to communicate with other services. Each microservice has its own data store and is deployed independently. Testing a microservices application requires a strategy that accounts not only for the isolated nature of microservices but also for service dependencies.
If you’ve managed reliability for either a microservices or a monolithic app, you know that – as we detailed in an earlier blog post – both types of environments come with their own reliability challenges. What can you do about those challenges? Which best practices should SREs adopt in order to simplify reliability for both microservices and monoliths? Read on for guidance.
The abundance of cloud services available today makes building web-scale products very accessible. Any company with sufficient resources can leverage infrastructure and platform services to build products that can serve thousands or even millions of customers. They can achieve economies of scale while providing a reliable service, without having to build everything from scratch.
If you’re responsible for a microservices app, you may be familiar with the idea of a “latency budget.” This is the maximum latency, measured as total request time, that you need for the app to work, in order to meet your SLAs and keep stakeholders happy. For a stock trading or financial services app, this budget might be the barest of microseconds.
This question was raised at the recent Redgate Summit: How does the implementation of a microservices architecture affect the implementation of a database DevOps approach? I could even rephrase it a little: Does a microservices architecture affect a database DevOps approach?
Microservices are a hot topic in the tech world and with good reason. These tiny systems form the backbone of a composable enterprise and most digital transformation strategies. They provide unmatched flexibility to businesses previously bound by monolithic application suites. But they present potential downsides when it comes to data management. In this article we’ll explore in more detail the relationship between microservices and master data management.
An IBM survey of IT executives, developer executives, and developers found that 87% of microservices users agreed that microservices adoption is worthwhile. Microservices are popular with both technology leaders and developers, making them a highly effective tool for businesses of all sizes. Microservices have many uses, and security is one area where micro services can both help — and harm.
I'm one of the fortunate people who have witnessed the (r)evolution of software development and delivery throughout my career. From programs deployed in local racks to serverless running with the pay-as-you-go paradigm, we've seen a breakthrough in computing in a relatively short time.
