I recently attended and presented at the east coast version of the Jenkins User Conference held this year in Washington, DC. The weather certainly fit the theme of the conference: The heat was continuous. The humidity was fully integrated with the heat. And, most importantly as you can see above, SWAG was out in full force.
Right from the opening keynote by the founder of Jenkins, Kohsuke Kawaguchi, this conference was jam-packed with all the latest capabilities of Jenkins, including discussions around the new capabilities like workflow, and several sessions on Linux containers, micro-services, and, everyone’s favorite topic, DevOps.
A smart APM strategy enlists the help from these three entities: the Witness, the Watchman, and the Agent. You start by listening to the testimony from the eye-witness (aka. wire data), collecting the observations from the watchman (aka. web robots), and analyzing details from the agent (aka. code level instrumentation).
In the world of Application Performance Management (APM) it is always better to enlist more than one entity to help solve the mystery of performance problems.
Overgrown applications have given way to modular applications, driven by the need to break larger problems into smaller problems. Similarly large monolithic development processes have been forced to be broken into smaller agile development cycles. Looking at trends in software development, microservices architectures meet the same demands.
Additional benefits of microservices architectures are compartmentalization and a limited impact of service failure versus a complete software malfunction. The problem is there are a lot of moving parts in these designs; this makes assuring performance complex especially if the services are geographically distributed or provided by multiple third parties.
The Internet of Things is not only adding billions of sensors and billions of terabytes to the Internet. It is also forcing a fundamental change in the way we envision Information Technology. For the first time, more data is being created by devices at the edge of the Internet rather than from centralized systems. What does this mean for today's IT professional?
In this Power Panel at @ThingsExpo, moderated by Conference Chair Roger Strukhoff, panelists addressed this very serious issue of profound change in the industry.
Those who are familiar with databases and persistence have probably had the same discussion like I have had a couple of times over the last couple of years:Do you use numeric or String values as an UUID?Having done a lot of distributed, multi-tenant development, my stance on this is very clear: I prefer String. Or better said, I prefer UUIDs.
A new book by Len Bass, Ingo Weber and Liming Zhu “DevOps: A Software Architect’s Perspective”, part of the SEI Series in Software Engineering, looks at how DevOps affects architectural decisions, and a software architect’s role in DevOps.
The authors focus on the goals of DevOps: to get working software into production as quickly as possible while minimizing risk, balancing...
The Chicago JUG has been doing a great job engaging with Adopt-a-JSR and Java EE 8. As part of that effort the JUG hosted a virtual meeting on Google Hangout on May 26. Some of the things that the meeting covered includes:
The Chicago JUG has been doing a great job engaging with Adopt-a-JSR and Java EE 8. As part of that effort the...
I suppose, the first case every developer learn in Mockito is mocking methods with return value. Construction when().thenReturn() covers 80% of all case in code I suppose. Next thing what developers learn in Mockito is mocking of void method. doAnswer().when() ussually used for this purpose.But I faced with rare case of using Mockito and want to share with it. Imagine that you...
There are many workflows for Git:
There are many workflows in Git. In this post, I will summarize four of the more popular ones: Centralized Workflow, Feature Branch Workflow, Gitflow, and Forking Workflow.
Sometimes we intentionally make our work more visible so that we can more easily see what’s going on. We do this so that, as a group, we get a better picture of the whole of the group’s effort. At it’s best, this is more than a dashboard that displays information. Instead, it’s a tool that’s used by the people doing the work in the process of doing that work.
Here in this article
we are trying to discuss about the finding reference object within stored
procedure and also finding the calling procedure references.
Developers are writing several stored procedures almost every day. Sometimes developers need to know about specific information within these stored procedures....
In our last post in the Definitive Guide to the Modern Database series, we examined three different trade-offs: In-memory vs. Disk-based; Scale-In vs. Scale-out, Consistent vs. Inconsistent; and SQL vs. NoSQL, “Classical” vs. “Modern.” Today let’s take a look at the final trade-off to consider when selecting a modern database.
Written by Tim Brock.
With all the hype around Big Data in recent years it's easy to assume that having more data is always an advantage. But as we add more and more data points to a scatter plot, we can start to lose these patterns and clusters. This problem, a result of overplotting, is demonstrated in the animation below. ...
the conditions that drive software project managers, development teams and
their leadership are often in the best interest of the company, they sometimes fail to recognize the software risks introduced to the
business by these decisions or behaviors. A review of the latest software
While the conditions that...
Internet of Things (IoT) will be a hybrid ecosystem of diverse devices and sensors collaborating with operational and enterprise systems to create the next big application.
In their session at @ThingsExpo, Bramh Gupta, founder and CEO of robomq.io, and Fred Yatzeck, principal architect leading product development at robomq.io, discussed how choosing the right middleware and integration strategy from the get-go will enable IoT solution developers to adapt and grow with the industry, while at the same time reduce Time to Market (TTM) by using plug and play capabilities offered by a robust IoT middleware platform.
I recently blogged about Injecting Kubernetes Services with CDI. In this post I am going to take things one step further and bring Apache Camel into the picture.
In this post I am going to take things one step further and bring Apache Camel into the picture. So, I am going to use Camel's CDI support to wire my...
Who cares about toString performance? Nobody! Except when you have huge amount of data being processed in a batch that does plenty of logging using toString . Then, you investigate why it’s slow, realize that the toString method is mostly implemented using introspection and can be optimized.
In the previous blog post about SolrCloud we’ve talked about the situation when ZooKeeper connection failed and how Solr handles that situation. However, we only talked about query time behavior of SolrCloud and we said that we will get back to the topic of indexing in the future. That future is finally here – let’s see what happens to indexing when ZooKeeper connection is not...
There was an interesting discussion recently on the jOOQ mailing list aboutjOOQ’s current lack of out-of-the-box support for TIMESTAMP WITH TIME ZONE data types.
There was an interesting discussion recently on the jOOQ mailing list aboutjOOQ’s current lack of out-of-the-box support for TIMESTAMP WITH TIME...
Logging on Docker has steadily evolved with each Docker
release and there are some exciting new updates that have come with
Docker 1.7 – for example, Docker 1.7 now includes new driver support for for Journald along with the driver support added with Docker 1.6 for JSON and syslog! We are here on the ground at DockerCon as part of the