TestOps – Assuring application quality at scale

The importance of TestOps

Continuous development, integration, testing, and deployment have become the norm for modern application development cycles. With the increased adoption of DevOps principles to accelerate release velocity, testing has shifted left to be embedded in the earlier stages of the development process itself. In addition, microservices-led application architecture has led to the adoption of shift right testing and testing individual services, and releases in the later stages of development, adding further complexity to the way quality is assured.

These challenges underline the need for automated testing. An increasing number of releases on one hand and an equally reducing release cycle times on the other have led to a strong need to exponentially increase the number of automated tests developed sprint after sprint. Although automation test suites reduce testing times, scaling these suites for large application development cycles mandates a different approach.

TestOps for effective DevOps – QA integration

In its most simplistic definition, TestOps brings together development, operations, and QA teams and drives them to collaborate effectively to achieve true CI/CD discipline. Leveraging four core principles across planning, control, management, and insights helps achieve test automation at scale.

  • Planning helps the team prioritize key elements of the release and analyze risks affecting QA like goals, code complexity, test coverage, and automatability. It’s an ongoing collaborative process that embeds rapid iteration for incorporating faster feedback cycles into each release.
  • Control refers to the ability to perform continuous monitoring and adjust the flow of various processes. While a smaller team might work well with the right documentation, larger teams mandate the need for established processes. Control essentially gives test ownership to the larger product team itself regardless of what aspect of testing is being looked at like functional, regression, performance, or unit testing.
  • Management outlines the division of activities among team members, establishes conventions and communication guidelines, and organizes test cases into actionable modules within test suites. This is essential in complex application development frameworks involving hundreds of developers, where continuous communication becomes a challenge.
  • Insight is a crucial element that analyses data from testing and uses it to bring about changes that enhance application quality and team effectiveness. Of late, AI/ML technologies have found their way into this phase of TestOps for better QA insights and predictions.

What differentiates TestOps

Unlike existing common notions, TestOps is not merely an integration of testing and operations. The DevOps framework already incorporates testing and collaboration right from the early stages of the development cycle. However, services-based application architecture introduces a wide range of interception points that mandate testing. These, combined with a series of newer test techniques like API testing, visual testing, and load and performance testing, slow down release cycles considerably. TestOps complements DevOps to plan, manage and automate testing across the entire spectrum, right from functional and non-functional testing to security and CI/CD pipelines. TestOps brings the ability to continuously test multiple levels with multiple automation toolsets and manage effectively to address scale.

TestOps effectively integrates software testing skillset and DevOps capability along with an ability to create an automation framework with test analytics and advanced reporting. By managing test-related DevOps initiatives, it can effectively curate the test pipeline, own it, manage effectively to incorporate business changes, and adapt faster. Having visibility across the pipeline through automated reporting capabilities also brings the ability to detect failing tests faster, driving faster business responses.

By sharply focusing on test pipelines, TestOps enables automatic and timely balancing of test loads across multiple environments, thereby driving value creation irrespective of an increase in test demand. Leveraging actionable insights on test coverage, release readiness, and real-time analysis, TestOps ups the QA game through root cause analysis of application failure points, obviating any need to crunch tons of log files for relevant failure information.

Ensure quality at scale with TestOps

Many organizations fail to consistently ensure quality across their application releases in today’s digital-first application development mode. The major reason behind this is their inability to keep up with test coverage of frequent application releases. Smaller teams ensure complete test coverage by building appropriate automation stacks and effectively collaborating with development and operations teams. For larger teams, this means laying down automation processes, frameworks, and toolsets to manage and run test pipelines with in-depth visibility into test operations. For assuring quality at scale, TestOps is mandatory. 

Does your QA approach meet your project needs at scale? Let’s talk

QE strategy to mitigate inherent risks involved in application migration to the cloud

Cloud migration strategies, be it lift & shift, rearchitect or rebuild, are fraught with inherent risks which need to be eliminated with the right QE approach

The adoption of cloud environments has been expanding for several years and is presently in an accelerated mode. A multi-cloud strategy is the defacto approach adopted by multiple organizations, as per Flexera 2022 State of the Cloud Report. The move toward cloud-native application architectures, exponential scaling needs of applications, and increased frequency and speed of product release launches have contributed to increased cloud adoption.

The success of migrating the application landscape to the cloud hinges on the ability to perform end-to-end quality assurance initiatives specific to the cloud. 

Underestimation of application performance

Availability, scalability, reliability, and high response rates are critical expectations from an application in a cloud environment. Application performance issues can come to light on account of incorrect sizing of servers or network latency issues that might not have surfaced when the application is tested in isolation. It can also be an outcome of an incorrect understanding of probable workloads that can be managed by an application while in a cloud environment. 

The right performance engineering strategy involves designing for performance in mind and fulfilling performance validations, including load testing. This ensures that the application under test remains stable in normal and peak conditions and defines and sets up application monitoring toolsets and parameters. There needs to be an understanding of workloads with the potential to be moved to the cloud and ones that need to remain on-premise. Incompatible application architectures need to be identified. Load testing should be carried out in parallel to record SLA response times across various loads for those moved to the cloud. 

Security and compliance

With the increased adoption of data privacy norms like GDPR and CCPA, there is a renewed focus on ensuring the safety of data migrated from application to cloud. Incidents like the one with Marriott hotel, where half a million sensitive customer information like credit cards and identity were compromised, have brought the need to test the security of data loaded onto cloud environments. 

A must-have element of a sound QA strategy is to ensure that both applications and data are secure and can withstand malicious attacks. With cybersecurity attacks increasing both in quantity and innovative tactics, there is a strong need for the implementation of security policies and testing techniques, including but not limited to vulnerability scanning, penetration testing, and threat and risk assessment. These are aimed at the following.

  • Identifying security gaps and weaknesses in the system
  • DDoS attack prevention
  • Provide actionable insights on ways to eliminate potential vulnerabilities

Accuracy of Data migration 

Assuring the quality of data that is being migrated to the cloud remains the top challenge, without which the convenience and performance expectation from cloud adoption falls flat. It calls for assessing quality before migrating, monitoring during migration, and verifying the integrity and quality post-migration. This is fraught with multiple challenges like migrating from old data models, duplicate record management, and resolving data ownership, to name a few. 

White-box migration testing forms a key component of a robust data migration testing initiative. It starts off by logically verifying a migration script to guarantee it’s complete and accurate. This is followed by ensuring database compliance with required preconditions, e.g., detailed script description, source, and receiver structure, and data migration mapping. Furthermore, the QA team analyzes and assures the structure of the database, data storage formats, migration requirements, the formats of fields, etc. More recently, predictive data quality measures have also been adopted to get a centralized view and better control over data quality. 

Application Interoperability

Not all apps that need to migrate to the cloud may be compatible with the cloud environment. Some applications show better performance in a private or hybrid cloud than in a public cloud. Some others require minor tweaking, while others may require extensive reengineering or recoding. Not identifying cross-application dependencies before planning the migration waves can lead to failure. Equally important is the need to integrate with third-party tools for seamless communication across applications without glitches. 

A robust QA strategy needs to identify applications that are part of the network, their functionalities, and dependencies among applications, along with each app’s SLA since dependencies between systems and applications can make integration testing potentially challenging. Integration testing for cloud-based applications brings to the fore the need to consider the following: 

  • Resources for the validation of integration testing 
  • Assuring cloud migration by using third-party tools
  • Discovering glitches in coordination within the cloud
  • Application configuration in the cloud environment
  • Seamless integration across multiple surround applications

Ensure successful cloud migration with Trigent’s QE services

Application migration to the cloud can be a painful process without a robust QE strategy. With aspects such as data quality, security, app performance, and seamless connection with a host of surrounding applications being paramount in a cloud environment, the need for testing has become more critical than ever. 

Trigent’s cloud-first strategy enables organizations to leverage a customized, risk-mitigated cloud strategy and deployment model most suitable for the business. Our proven approach, frameworks, architectures, and partner ecosystem have helped businesses realize the potential of the cloud.

We provide a secure, seamless journey from in-house IT to a modern enterprise environment powered by Cloud. Our team of experts has enabled cloud transformation at scale and speed for small, medium, and large organizations across different industries. The transformation helps customers leverage the best architecture, application performance, infrastructure, and security without disrupting business continuity. 

Ensure a seamless cloud migration for your application. Contact us now!

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