This whitepaper outlines how DevOps practices can be extended to the IT team, and the cultural shift required to capture the business value of Compliant Database DevOps.
Static analysis is a powerful way to harden software, finding bugs and security vulnerabilities at the earliest stage of software development. But how do you start? Read this guide to learn how to systematically introduce and integrate an advanced static analysis tool into your project, successfully.
Learn why and how Continuous Testing's real-time objective assessment of an application's business risks is a critical component of DevOps.
5 Key Capabilities Your API Testing Solution Should Have - Choosing the right API testing solution for your organization can be a daunting challenge when you take into account all of the features and capabilities to consider. For more guidance and details, download our guide to the key features that must be included in your API testing solution to ensure a successful rollout across your organization.
Test Data Management (TDM) is a big problem for organizations, with the process of procuring, owning, and securing test data both a requirement and a liability. Parasoft provides a modernized solution to solve these problems. Parasoft’s data simulation approach combines traditional test data extraction along with service virtualization, all in an easy-to-use web interface, so users can quickly build meaningful test data by capturing realistic test data from interactions between components in their existing system, and building data models that can be shared and controlled directly by testing teams. Download this white paper to learn more.
To provide the DevOps community an objective perspective on what quality metrics are most critical for DevOps success, Tricentis commissioned Forrester to research the topic. Forrester analyzed how DevOps leaders use and value 75 common quality metrics—then identified which metrics matter most for DevOps success. This ebook takes a deep dive into the findings from that research. Read it to learn:
- How the metrics compare…visualized with heat maps and quadrant plots
- If you’re relying on “overrated” metrics or missing “hidden gems”
- What metrics are the most significant “DevOps differentiators” separating DevOps leaders from laggards
Download this new whitepaper to discover the ROI of Compliant Database DevOps, the business value to be gained, and how it’s viewed from the perspective of a CEO, a CIO, or an IT manager. Paragraph description: What business benefits can Compliant Database DevOps bring your organization? How can you deliver value faster, whilst keeping data safe? This whitepaper illustrates the business value that can be realized and how it is viewed from the perspective of a CEO, a CIO, or an IT Manager. Using industry averages, the paper provides working examples of introducing DevOps practices across different stages of the database development and deployment process to calculate the ROI of Compliant Database DevOps. Download the whitepaper.
This report helps application leaders understand what’s needed to transform software for Agile and DevOps — with a focus on the role of Continuous Testing, SAP testing, and end-to-end testing across packaged apps, UI, APIs, mobile, and more. Download the complete report to learn:
- The critical capabilities for software testing tools
- How vendors compare across core capabilities and use cases
- Gartner’s insights on “enterprise end-to-end testing”: the ability to test across all layers of an application such as web or mobile device front ends, business logic layers (e.g., SAP), APIs, and cloud services components within a single console.
All the latest insights on DevOps adoption rates among SQL Server Professionals. Read the report to understand the challenges – and the opportunities – of adopting database DevOps alongside broader DevOps initiatives Paragraph description: This report contains the results of the latest annual survey SQL Server database professionals, across a range of industries and company sizes. Over 1000 organizations were asked whether they had adopted DevOps practices and if they had extended the same principles to databases. The responses give an understanding of the challenges – and the opportunities – of adopting Database DevOps, looking at how things have developed over the last 12 months, and what key challenges and requirements are driving DevOps adoption in 2019.
Download a complimentary copy of the 2017 Gartner Magic Quadrant for Software Test Automation.
The database DevOps magazine from Redgate Software explores the new world of compliant Database DevOps, and how to protect against data breaches without turning the database into a deployment bottleneck.
Tricentis commissioned Forrester to evaluate current software development and delivery priorities as well as key metrics tracked throughout the software development lifecycle. Download the report to learn:
- What 5 core Continuous Testing practices separate Agile/DevOps leaders from laggards
- How Continuous Testing practice usage & automation varies across leaders and laggards
- Where automation has the greatest impact on DevOps success
- About the dangerous “risk blind spot” in most organizations
- What quality metrics are most valuable at each phase of the delivery process
There is, inevitably, a cost to introducing database DevOps, but what kind of return can you expect from that investment? Redgate used some pioneering research into the real business benefits of DevOps, and calculated the actual $ cost from some real-world examples, to show the return for every stakeholder involved.
DevOps is becoming the new normal in application development, and DevSecOps is now entering the picture. By balancing the desire to release code faster with the need for the same code to be secure, it addresses increasing demands for data privacy. But what about the database? How can databases be included in both DevOps and DevSecOps? What additional measures should be considered to achieve truly compliant database DevOps? This whitepaper provides a valuable insight.
Software testing might not be as exciting as development, where abstract ideas are magically transformed into attractive interfaces you can showcase to customers and staff. However, testing can have a tremendous impact on the success of your digital transformation strategy. In fact, testing is often the silent killer of these efforts. Why? Because software testing is still dominated by yesterday’s tools and outdated processes — which don’t meet the needs of today’s accelerated development processes. Learn how this disconnect results in:
- Throttled acceleration
- Risk to your brand
- Poorly-allocated resources
Continuous integration and automated deployments become possible with database DevOps, paving the way to a complete continuous delivery process. Importantly, the biggest roadblock isn’t the hardware or software you require, it’s the development practices and strategies that need to change to accommodate it. This whitepaper gives some practical tips to introducing continuous delivery and including the database in your DevOps journey.
This report contains the results of Redgate's latest annual survey SQL Server database professionals, across a range of industries and company sizes. Over 700 organizations were asked whether they had adopted, or were planning to adopt, DevOps practices and how many of them had applied the same principles to their databases. The report looks at how things have developed over the last 12 months, and what key challenges and requirements are driving DevOps adoption in 2018.
For over two decades now, software testing tool vendors have been tempting enterprises with the promise of test automation. However, the fact of the matter is that most companies have never been able to achieve the desired business results from their automation initiatives. Recent studies report that test automation rates average around 20% overall, and from 26-30% for agile adopters. Read this paper to explore the 6 factors contributing to these dismal automation results — and insights into the best path forward.
Although Artificial Intelligence (AI) is nothing new, applying AI techniques to software testing started to become feasible just the past couple years. Inevitably, AI will soon become part of our day-to-day quality engineering process. But before we get caught up in the exuberance of the technology, let’s take a step back and assess how AI can help us achieve our quality objectives. It’s been suggested that AI could be applied to actions such as prioritizing testing and automation, generating and optimizing test cases, enhancing UI testing, reducing tedious analysis tasks, and helping to determine pass/fail outcomes for complex and subjective tests. However, should AI be applied in these cases? And where else could it assist?
The Software Fail Watch is an analysis of software bugs found in a year’s worth of English language news articles. The result is an extraordinary reminder of the role software plays in our daily lives, the necessity of software testing in every industry, and the far-reaching impacts of its failure. The 5th Edition of the Software Fail Watch identified 606 recorded software fails, impacting half of the world’s population (3.7 billion people), $1.7 trillion in assets, and 314 companies. And this is just scratching the surface — there are far more software bugs in the world than we will likely ever know about. Download the report for a detailed analysis of 2017 software fails, including:
- The overall impact on businesses, users, time, and assets
- How the number and type of software fails compare to previous years
- Software fail trends within and across industries — finance, retail, consumer tech, services (e.g., internet, telecom), public services, healthcare, transportation, and entertainment
- The biggest stories, hacks, and glitches that made headlines or slipped under the radar