64 items found: Search results for "performance" in all categories x
August 24, 2016 | Cassandra
At OpenCredo we are seeing an increase in adoption of Apache Cassandra as a leading NoSQL database for managing large data volumes, but we have also seen many clients experiencing difficulty converting their high expectations into operational Cassandra performance. Here we present a high-level technical overview of the major strengths and limitations of Cassandra that we have observed over the last few years while helping our clients resolve the real-world issues that they have experienced.
February 13, 2012 | Software Consultancy
Recently we were approached by a client to do some performance testing of the web application they had written. The budget allowed two days for this task. Ok. No problem. Yes, we can. Naturally I had one or another question though…
February 16, 2023 | Blog, Data Analysis, Neo4j
Check out Part 2 of Ebru Cucen and Fahran Wallace’s blog series, in which they discuss their experience ingesting 400 million nodes and a billion relationships into Neo4j and what they discovered along the way.
January 26, 2023 | Blog, Data Analysis, Neo4j
Fahran Wallace and Ebru Cucen’s most recent blog post is part 1 of a three-part series. They investigate how OpenCredo ingested 400 million nodes with a billion relationships into Neo4j.
Read Matt Farrow’s blog as he explores the potential for using Open Policy Agent to filter and mask data being sent to and read from Apache Kafka.
May 12, 2022 | Microservices
Combining Native image with Spring Boot and Micronaut GraalVM makes for a high-performance runtime that can significantly improve application performance and efficiency, making it ideal for microservices. Native images enable Java applications to be compiled ahead of time, resulting in smaller, faster Java microservices.
In this talk, Guy Coleman will demonstrate a hello world web service using both Spring Boot and Micronaut as they both support native images.
January 31, 2022 | Blog, Data Engineering
There are two camps of Graph database, one side is RDF, where they are strict with their format, and somewhat limited for their extensibility. The other side is LPG, where they can define labels to the relationships. With its recent extension, RDF now allows users to add properties, thus becoming RDF*. In this blog, Ebru explores the structural and performance differences between LPG and RDF*.
December 5, 2021 | Cloud, Kubernetes
Kubernetes’ second release in 2021, version 1.22, has been out for a little while now and with 1.23 on its way, we thought we’d take a look back. Kubernetes 1.22 was a highly comprehensive release with 53 enhancements in all three graduation levels: 13 features have graduated to stable, 24 enhancements reached beta status, and 16 new features have been accepted into the alpha stage.
The latest version has some noteworthy security features such as running Kubelet without root access, pod security policies, and seccomp. There are also a couple of deprecated and removed APIs. In this blog, we’ll discuss the significant changes in v1.22, as well as how to handle the removed APIs.
April 20, 2021 | Data Engineering, Machine Learning, Software Consultancy
Our recent client was a Fintech who had ambitions to build a Machine Learning platform for real-time decision making. The client had significant Kubernetes proficiency, ran on the cloud, and had a strong preference for using free, open-source software over cloud-native offerings that come with lock-in. Several components were spiked with success (feature preparation with Apache Beam and Seldon for model serving performed particularly strongly). Kubeflow was one of the next technologies on our list of spikes, showing significant promise at the research stage and seemingly a good match for our client’s priorities and skills.
That platform slipped down the client’s priority list before completing the research for Kubeflow, so I wanted to see how that project might have turned out. Would Kubeflow have made the cut?
February 17, 2021 | Blog, Cloud, Cloud Native, GCP, Open Source
Multi-cloud is rapidly becoming the cloud strategy of choice for enterprises looking to modernise their applications.
And the reason is simple – it gives them much more flexibility to host their workloads and data where it suits them best.
In this post, we focus on Google’s application modernisation solution Google Anthos and the role it can play in your cloud transformation strategy.
December 11, 2020 | Cloud, Cloud Native, Kubernetes, Microservices
“WebAssembly is a safe, portable, low-level code format designed for efficient execution and compact representation.” – W3C
In this blog, I’ll cover the different applications of Wasm and WASI, some of the projects that are making headway, and the implications for modern architectures and distributed systems.
October 15, 2020
Continuous Verification is a term that is starting to pop up from time-to-time… but what does it mean? Well… according to Nora Jones and Casey Rosenthal, authors of O’Reilly’s Chaos Engineering books,
“Continuous verification (CV) is a discipline of proactive experimentation, implemented as tooling that verifies system behaviors. This stands in contrast to prior common practices in software quality assurance, which favor reactive testing, implemented as methodologies that validate known properties of software. This isn’t to say that prior common practices are invalid or should be deprecated. Alerting, testing, code reviews, monitoring, SRE practices, and the like—these are all great practices and should be encouraged”
Over the course of this post, we will unpack this statement: to understand what is behind it and what it might mean for your development process.
September 22, 2020 | AWS, Blog, Cassandra, Cloud, DevOps, Open Source
With the upcoming Cassandra 4.0 release, there is a lot to look forward to. Most excitingly, and following a refreshing realignment of the Open Source community around Cassandra, the next release promises to focus on fundamentals: stability, repair, observability, performance and scaling.
We must set this against the fact that Cassandra ranks pretty highly in the Stack Overflow most dreaded databases list and the reality that Cassandra is expensive to configure, operate and maintain. Finding people who have the prerequisite skills to do so is challenging.
March 20, 2020
Traditionally, Usability and Security have been set in opposition to each other: with tight security, we end up with painful user experience. In this blog, Guy focuses on financial services as an exemplar of how we can introduce usability into a vertical with challenging security and compliance requirements.
October 3, 2019
Continuing on from Stuart’s previous blog which covered highlights from CloudNative London conference day 1, I have put together a summary for day 2.
Being an OCer (OpenCredo employee) has given me the opportunity to fully embed myself in the London technology scene. Alongside our direct engagements with clients, it is a chance to understand and evaluate the trends and lessons that have emerged over the past year.
For conferences and technical content, London is a very crowded location. Every day it seems like a new conference is being announced and I know I cannot attend them all, no matter how much I want too! Alongside some of my other colleagues, I was given the option to attend the Skillsmatter CloudNative London conference and with the increase of organisations embracing the dynamic and transformative benefits offered by an ever-growing choice of cloud providers, it seemed like a good fit.
May 16, 2018 | Microservices
To identify service boundaries, it is not enough to consider (business) domains only. Other forces like organisational communication structures, and – very important – time, strongly suggest that we should include several other criteria in our considerations.
January 23, 2018 | Data Engineering, DevOps
Machine Learning is a hot topic these days, as can be seen from search trends. It was the success of Deepmind and AlphaGo in 2016 that really brought machine learning to the attention of the wider community and the world at large.
October 24, 2017 | Data Engineering
Cockroach Labs, the creators of CockroachDB are coming to London for the first time since their 1.0 GA Release in May 2017. They will be taking time to talk about “The Hows & Whys of a Distributed SQL Database” at the Applied Data Engineering meetup, hosted and run by us here at OpenCredo.
We have been interested in CockroachDB for a while now, including publishing our initial impressions of the release on our blog. We thought this would be the perfect time to do a bit of a Q&A before the event! I posed Raphael Poss, a core Software Engineer at Cockroach Labs a few questions.
August 8, 2017 | Cassandra
Recently, the sad news has emerged that Basho, which developed the Riak distributed database, has gone into receivership. This would appear to present a problem for those who have adopted the commercial version of the Riak database (Riak KV) supported by Basho.
This blog is written exclusively by the OpenCredo team. We do not accept external contributions.
July 11, 2017 | Cloud, Cloud Native
Over the years, OpenCredo’s projects have become increasingly tied to the public cloud. Our skills in delivering cloud infrastructure and cloud native applications have deepened and the range of cloud projects we are able to take on has grown. From enterprise cloud brokers to cloud platform migration in restricted compliance environments, our ability to deliver on the cloud is now a core component of our value proposition.
June 15, 2017 | Data Engineering
CockroachDB is a distributed SQL (“NewSQL”) database developed by Cockroach Labs and has recently reached a major milestone: the first production-ready, 1.0 release. We at OpenCredo have been following the progress of CockroachDB for a while, and we think it’s a technology of great potential to become the go-to solution for a having a general-purpose database in the cloud.
May 9, 2017 | Cassandra
Data analytics isn’t a field commonly associated with testing, but there’s no reason we can’t treat it like any other application. Data analytics services are often deployed in production, and production services should be properly tested. This post covers some basic approaches for the testing of Cassandra/Spark code. There will be some code examples, but the focus is on how to structure your code to ensure it is testable!
This blog is written exclusively by the OpenCredo team. We do not accept external contributions.
May 2, 2017 | Cassandra, Data Engineering
My recent blogpost I explored a few cases where using Cassandra and Spark together can be useful. My focus was on the functional behaviour of such a stack and what you need to do as a developer to interact with it. However, it did not describe any details about the infrastructure setup that is capable of running such Spark code or any deployment considerations. In this post, I will explore this in more detail and show some practical advice in how to deploy Spark and Apache Cassandra.
March 7, 2017 | Data Analysis, GCP
Google has recently made its internal Spanner database available to the wider public, as a hosted solution on Google Cloud. This is a distributed relational/transactional database used inside for various Google projects (including F1, the advertising backend), promising high throughput, low latency and 99.999% availability. As such it is an interesting alternative to many open source or other hosted solutions. This whitepaper gives a good theoretical introduction into Spanner.
February 28, 2017 | Software Consultancy
As Kotlin’s 1.1 release draws closer, I’ve been looking at some of the new language features it supports. Type aliases may seem like a relatively minor feature next to coroutines, but as I will show in this blog post, they can open up a new programming idiom, particularly when combined with extension functions.
February 16, 2017 | Cassandra
One of the default Cassandra strategies to deal with more sophisticated queries is to create CQL tables that contain the data in a structure that matches the query itself (denormalization). Cassandra 3.0 introduces a new CQL feature, Materialized Views which captures this concept as a first-class construct.
February 13, 2017 | Data Engineering
One of the stated intentions behind the design of Java 8’s Streams API was to take better advantage of the multi-core processing power of modern computers. Operations that could be performed on a single, linear stream of values could also be run in parallel by splitting that stream into multiple sub-streams, and combining the results from processing each sub-stream as they became available.
January 25, 2017 | Cassandra
One of the simplest and best-understood models of computation is the Finite State Machine (FSM). An FSM has fixed range of states it can be in, and is always in one of these states. When an input arrives, this triggers a transition in the FSM from its current state to the next state. There may be several possible transitions to several different states, and which transition is chosen depends on the input.
October 13, 2016 | Data Analysis
In Lisp, you don’t just write your program down toward the language, you also build the language up toward your program. As you’re writing a program you may think “I wish Lisp had such-and-such an operator.” So you go and write it. Afterward you realize that using the new operator would simplify the design of another part of the program, and so on. Language and program evolve together…In the end your program will look as if the language had been designed for it. And when language and program fit one another well, you end up with code which is clear, small, and efficient – Paul Graham, Programming Bottom-Up
October 10, 2016 | Cassandra
In the culmination of our blog series on the topic, on October 6th 2016 OpenCredo Consultants Dominic Fox, Alla Babkina and Guy Richardson, and hosted by Marco Cullen, presented the common design and implementation issues that they have come across in real-world Apache Cassandra deployments.
September 27, 2016 | Cassandra, Data Engineering
If there is one thing to understand about Cassandra, it is the fact that it is optimised for writes. In Cassandra everything is a write including logical deletion of data which results in tombstones – special deletion records. We have noticed that lack of understanding of tombstones is often the root cause of production issues our clients experience with Cassandra. We have decided to share a compilation of the most common problems with Cassandra tombstones and some practical advice on solving them.
September 15, 2016 | Cassandra
Cassandra isn’t a relational database management system, but it has some features that make it look a bit like one. Chief among these is CQL, a query language with an SQL-like syntax. CQL isn’t a bad thing in itself – in fact it’s very convenient – but it can be misleading since it gives developers the illusion that they are working with a familiar data model, when things are really very different under the hood.
September 6, 2016 | Cassandra
A growing number of clients are asking OpenCredo for help with using Apache Cassandra and solving specific problems they encounter. Clients have different use cases, requirements, implementation and teams but experience similar issues. We have noticed that Cassandra data modelling problems are the most consistent cause of Cassandra failing to meet their expectations. Data modelling is one of the most complex areas of using Cassandra and has many considerations.
June 15, 2016 | Software Consultancy
It’s as simple as that – and as a consultant, it’s a problem I see all the time. Testing is always focused on functional testing. Non-functional testing, by comparison, is treated like a second class citizen. This means that functional requirements get refined, and non-functional requirements are ignored until the very end.
April 28, 2016 | Software Consultancy
In a conventional RDBMS-with-ORM system, we are used to thinking of domain objects as mapped to rows in database tables, and of the database as a repository where the current state of every object exists simultaneously, so that what we get when we query for an object is the state that object was in at the time the query was issued. To perform an update, we can start a transaction, retrieve the current state of the object, modify it, save it back again and commit. Transactions move the global state of the system from one consistent state to another, so that the database transaction log represents a single, linear history of updates. We are therefore able to have a very stable, intuitive sense of what it means to talk about the “current state” of any domain object.
April 5, 2016 | Software Consultancy
This post is part of a series which introduce key concepts in successful test automation. Each post contains sample code using the test-automation-quickstart project, a sample Java test automation framework available from Github.
March 2, 2016 | DevOps, Microservices
Many of our clients are currently implementing applications using a ‘microservice’-based architecture. Increasingly we are hearing from organisations that are part way through a migration to microservices, and they want our help with validating and improving their current solution. These ‘microservices checkup’ projects have revealed some interesting patterns, and because we have experience of working in a wide-range of industries (and also have ‘fresh eyes’ when looking at a project), we are often able to work alongside teams to make significant improvements and create a strategic roadmap for future improvements.
March 2, 2016 | Microservices
Microservice-style software architectures have many benefits: loose coupling, independent scalability, localised failures, facilitating the usage of polyglot data persistence tools or multiple programming languages.
However, they also introduce other challenges. A major one is the fact that the end-user functionality of the system will ultimately emerge as a composition of multiple services. This significantly increases the complexity of deploying the system. In addition, because we lose the concept of “versions” of the system, it becomes harder to answer questions like “what capabilities are in production?” and “when is a new feature considered ‘done’?”.
January 26, 2016 | Data Engineering
In this second post about Hazelcast and Spring, I’m integrating Hazelcast and Spring-managed transaction for a specific use case: A transactional Queue. More specifically, I want to make the message polling, of my sample chat application, transactional.
January 15, 2016 | Software Consultancy
January 8, 2016 | Microservices
Many of our clients are in the process of investigating or implementing ‘microservices’, and a popular question we often get asked is “what’s the most common mistake you see when moving towards a microservice architecture?”. We’ve seen plenty of good things with this architectural pattern, but we have also seen a few recurring issues and anti-patterns, which I’m keen to share here.
December 16, 2015 | Cloud, DevOps
In the rush to embrace DevOps, many organisations seek out tools to help them achieve DevOps nirvana; the magical tools that will unify Development and Operations, stop the infighting, and ensure collaboration. This search for tools to solve problems exists in many domains, but seems particularly prevalent in IT (it may be real, or a reflection of my exposure to IT). The temptation to embrace new tools as a panacea is high, because the problems in IT seem so pervasive and persistent.
December 1, 2015 | Software Consultancy
This post introduce some of the basic features of Hazelcast, some of its limitations, how to embed it in a Spring Boot application and write integration testings. This post is intended to be the first of a series about Hazelcast and its integration with Spring (Boot). Let’s start from the basics.
October 31, 2015 | Microservices
Over the past few weeks I’ve been writing an OpenCredo blog series on the topic of “Building a Microservice Development Ecosystem”, but my JavaOne talk of the same title crept up on me before I managed to finish the remaining posts. I’m still planning to finish the full blog series, but in the meantime I thought it would be beneficial to share the video and slides associated with the talk, alongside some of my related thinking. I’ve been fortunate to work on several interesting microservice projects at OpenCredo, and we’re always keen to share our knowledge or offer advice, and so please do get in touch if we can help you or your organisation.
October 18, 2015 | Cloud, DevOps
Last week Steve Poole and I were once again back at the always informative JAX London conference talking about DevOps and the Cloud. This presentation built upon our previous DevOps talk that was presented last year, and focused on the experiences that Steve and I had encountered over the last year (the slides for our 2014 “Moving to a DevOps” mode talk can be found on SlideShare, and the video on Parleys).
October 16, 2015 | Software Consultancy
OpenCredo is helping Skillsmatter with the organisation of the inaugural ContainerSched conference, and we were last night in attendance at CodeNode, working our way to finalising the program alongside the Skillsmatter team. I’m pleased to say that the provisional lineup looks great (speaker acceptance emails are being sent out over the next few days), and so I wanted to share the details of some of the great content we have confirmed already.
August 5, 2015 | Data Analysis, Data Engineering
A few weeks ago, we thought about building a Google analytics dashboard to give us easy access to certain elements of our Google Analytics web traffic. We saw some custom dashboards for bloggers, but nothing quite right for our goal, since we wanted the data on a big screen for everyone in the office to view.
August 5, 2015 | Cloud, GCP, Kubernetes
Why OpenCredo partnered with Google
Recently OpenCredo chose to partner with Google in order to share knowledge and resources around the Google Cloud Platform offerings. Our clients come in many shapes and sizes, but typically all of them realise three disruptive truths of the modern IT industry: the (economic) value of cloud; the competitive advantage of continuous delivery; and the potential of hypothesis and data-driven product development to increase innovation (as popularised by the Lean Startup / Lean Enterprise motto of ‘build, measure, learn’).
July 14, 2015 | Software Consultancy
Building simple proxies
In the previous post I introduced Java dynamic proxies, and sketched out a way they could be used in testing to simplify the generation of custom Hamcrest matchers. In this post, I’m going to dive into some techniques for implementing proxies in Java 8. We’ll start with a simple case, and build up towards something more complex and full-featured.
July 8, 2015 | Software Consultancy
November 21, 2014 | White Paper
In our latest white paper we cover the high level fundamentals of test automation, discuss the primary problems test automation solves and take a look at the steps required to implement this within your development process – all aimed at improving software delivery.
November 19, 2014 | Microservices
Undeniably, there is a growing interest in microservices as we see more organisations, big and small, evaluating and implementing this emerging approach. Despite its apparent novelty, most concepts and principles underpinning microservices are not exactly new – they are simply proven and commonsense software development practices that now need to be applied holistically and at a wider scale, rather than at the scale of a single program or machine. These principles include separation of concerns, loose coupling, scalability and fault-tolerance.
November 4, 2014 | Software Consultancy
When starting a project, teams often spend their time re-inventing the ‘automated testing wheel’. While every project has it’s own challenges and every team it’s own needs, many things exist as common requirements of a flexible test automation framework.
This post introduces an effective Java test framework that can be used to quickly get started with test automation on a Java project.
December 2, 2013 | Cassandra
Perhaps the most important of Cassandra’s selling points is its completely distributed architecture and its ability to easily extend the cluster with virtually any number of nodes. Implementing a classical RDBMS-style transaction consisting of “put locks on the database, modify the data, then commit the transaction”-style operations are simply not feasible in such an architecture (i.e. that doesn’t scale well).
November 6, 2013 | Software Consultancy
In many organisations, development and test teams have a ready answer for this, and that answer is usually wrong. Commonly, teams use test counts and code coverage statistics, which alone are not enough to validate a test approach and run the risk of giving a false sense of security to stakeholders. In practice, we are not able to fully prove the efficacy of our test strategy until after a release. Once software is in use, new defects highlight where our tests are failing to validate the software and where we need to invest effort to improve coverage. This is where many teams fail to learn and improve.
February 25, 2013 | Neo4j
As part of our work, we often help our customers choose the right datastore for a project. There are usually a number of considerations involved in that process, such as performance, scalability, the expected size of the data set, and the suitability of the data model to the problem at hand.
This blog post is about my experience with graph database technologies, specifically Neo4j. I would like to share some thoughts on when Neo4j is a good fit but also what challenges Neo4j faces now and in the near future.
February 19, 2013 | Software Consultancy
This blog post continues on from Part 1 which discussed types of tests and how to create robust tests. Part 2 will examine techniques to help whip a test suite in to shape and resolve common issues that slow everything down. The approaches in this post will focus on spring based applications, but the concepts can be applied to other frameworks too.
January 7, 2013 | Software Consultancy
The practice of continuous integration in which build servers are used to build and perform testing of code is now widespread and mainstream.
While not all teams have adopted continuous integration effectively, its increasing adoption has led many to start to look for additional opportunities to improve the cost, quality and speed of delivery with which software targeted to meet business needs can be released into production environments.
Traditionally Continuous Integration addresses the question of “does the software build and pass our unit and integration test suites?”. This is often insufficient.
December 18, 2012 | Software Consultancy
The first thing most people think of when they start a project with the good intentions of test driven development is: write a test first. That’s great, and something I would fully encourage. However, diving in to writing tests without forethought, especially on large projects with a lot of developers can lead to new problems that TDD is not going to solve. With some upfront thinking (but not big upfront design!) a large team can avoid problems later down the line by considering some important and desirable traits of a large and rapidly changing test suite.
November 4, 2011 | Neo4j
In the previous post we compared the performance of fetching relationships from densely populated nodes using Neo4j native store and using lucene index.
We’ve seen that we can fetch the small subset of relationships from a super-node (containing ~1M relationships in total) directly from the Lucene index, the performance of the first run (cold-caches) is better then using the Neo store directly. The subsequent runs with caches warmed up show comparable performance, slightly in favor of direct Neo store fetching, sue to low level cache optimizations.
June 3, 2011 | Neo4j
Neo4J is one of the first graph databases to appear on the global market. Being open source, in addition to its power and simplicity in supporting graph data model it represents good choice for production-ready graph database.
However, there has been one area I have struggled to get good-enough performance from Neo4j recently – super nodes.