More than 1 million developers, engineers and industry leaders set the trends for 2017, which topics interested you the most?
Before we get into announcing the contenders for the most influential post of the year, we also want to share some of the noteworthy milestones we experienced here at OverOps in 2017. Out of everything, some of the most exciting moments this year included closing out our Series C funding round after raising $30 million, receiving Gartner’s Cool Vendor Award and introducing our .NET Beta.
Aside from all of that, our OverOps families in San Francisco and Tel Aviv grew to nearly double their size at this time last year, we attended and spoke at conferences around the country and had the opportunity to interact with countless bright and motivated developers and engineers along the way.
But enough about us! Let’s introduce the categories included in this year’s Java Community Oscars:
- Java 9 GA Release
- Popular Tool Comparisons
- Trends in Tech
- Data Crunch
— OverOps (@overopshq) December 27, 2017
Java 9 GA Release
We’re known to cover topics from Java to Scala (to .NET) and everything in between, but the obvious fan favorites this year were our deep dives into new features and intricacies of the much-anticipated Java 9 release. If you missed it and you need to catch up, you can read everything you need to know about the new modular system right here.
Some of the new features introduced in Java 9 are expected to shift both the way new code is written plus the way the Java platform will evolve itself. First and foremost, Project Jigsaw is finally here! Plus, the new Stack-Walking API will change the way we traverse stack traces, and the future development of Java was turned on its head with the introduction of Incubator Modules and Project Amber.
Incubator modules will open discussion and development of new features to the wider Java community, as non-standardized features will be accessible in incubator modules. Project Amber is a similar project targeted towards the official Java development team to help with new language features like local variable type inference and enhanced enums.
Lastly, we would be remiss to not give an honorable mention to our post covering C# features missing from Java. This post generated one of the most lively comment sections we’ve seen here for years. You may not agree with all of our points there (or any of them), but the battle for the best programming language must go on!
Popular Tool Comparisons
This industry moves fast, sometimes it feels like there are new tools coming out every day, all promising to be the best for teams shifting to high frequency releases or moving their monolith application to microservices. This year, we covered the tools surfacing in some of the most disrupted corners of the tech industry: CI/CD, anomaly detection, cloud-native application deployment and more.
So, which trend do you most want to keep up with as successful Java developer teams? Drum roll, please…………… CI/CD workflows!
Our most popular tools comparison post this year looked at the pros and cons of using Jenkins vs Travis CI vs Circle CI vs TeamCity vs Codeship vs GitLab CI vs Bamboo for implementing CI/CD workflows. Whether you’re new to the CI/CD scene or you’ve been here all along, get the lowdown on each of these popular tools to see what each of them have to offer.
Looking instead for a deployment platform for cloud-native applications? In this post comparing Pivotal Cloud Foundry and Kubernetes, we looked at the differences and similarities to help you discover which tools will work best for you based on your team’s preferences and needs.
And, of course, always a popular topic… Which tools should you use to analyze all of the data that you’ll be looking at AFTER deployments. For an introduction into the world of data visualization, check out our comparison of Grafana and Kibana in which guest author Chris Ward covers everything from getting started to data sources to visualization and community.
If you’re already using one (or both) of those tools for your data visualization, you might be more interested in reaching new heights with your analysis. This post is about 5 new Java anomaly detection tools that can help you cut through noisy data to detect, and even predict, when anomalies occur.
Trends in Tech
Every year, new tools pop up ready to answer the plea of developers in need, ready to address the needs brought on by a new way of writing, deploying or monitoring code. This year was no exception.
One of the hottest trends of the year was the acceleration of CI/CD in the industry. Everybody wants to speed up the deployment process so that new code and, hence, new features, can get to the market even fast. So, we addressed the elephant in the room, what’s the one thing that keeps breaking your CI/CD workflow? Get all the deets in this top post from 2017.
Of course, deployment isn’t the only important part of application development. Where would we be without monitoring and troubleshooting? One trend that caught our attention this year (and yours too, it seems) is the Exception Inbox Zero Policy. The basic idea is that no exception, error or bug goes unnoticed or unhandled. What an exceptional strategy!
Last on the list for industry trends is one that is starting to trend in just about every industry there is. Artificial intelligence and genetic algorithms stand to impact just about every facet of human life. So, it’s not hard to guess why our post about solving tough problems using genetic algorithms was such a hit!
Once a winner, always a winner, right? Our top 100 Java libraries on Github (2017 edition) was one of our top ranking posts again this year. It’s not difficult to figure out why. One of our hobbies here at OverOps is to spend late nights going over data, and it seems that our readers share our passion for numbers.
GitHub is a source of bountiful data and often fuels our needs to crunch the numbers. If you’re intrigued by common logging practices and missteps, check out our posts analyzing logging behavior on GitHub too, we compared the usage of string concatenation vs parameterized logging plus took a closer looks at why more than 50% of logging statements being used incorrectly.
Not all data, though, comes from GitHub. Another one of our popular research-heavy posts this year was one that looked at a study of the top causes for unhappiness among developers. The research is based off of a survey that included more than 2,000 developers from close to 90 different countries. In this post, we outlined some of the major findings.
The end of 2017 is here, and thus, it is a time for reflection. It’s a time to look back on the ups and downs, the deployments and the crashes… It’s time for us to grow from our successes and learn from our mistakes.
Ok, enough of that, we need to start looking forward. Let us know what your favorite post from 2017 was in the comments below and what you’re most looking forward to hearing about in 2018!