DevOps & DataOps best practicesLast updated on November 10, 2019
Investing in software development not just implies to putting in money for the sake of getting one but it is beyond just a sheer investment. Seeing numerous businesses growing each day, to pick up the right beat and stay ahead your competitors is what you all need. Right?
You have knocked the right door if you want to boost growth in your organization, exponentially! Ensuring the quality, performance, security, as well as integrity in any system, can only be achieved if you strike the right chord of the technological instrument. Well, as we all know, innovation enables to envision a change as an opportunity and this statement is truly demonstrated by DevOps & DataOps technology. With the need to comprehensively build and deploy software as well as the data, DevOps and DataOps methodology came into existence, which gives a holistic approach to the actual working. Implementing DevOps and DataOps in an organization pipelines all the activities that contribute to its betterment.
Well, to give you a brief about what DevOps and DataOps refer to, here it is:
DevOps aims to enhance the execution process of software starting from its design to its construction, testing and delivery. DataOps is an extension of DevOps technology which aims to revolutionize data and its operations like storing, processing voluminous data and performing analytics.
Both DevOps & DataOps, define a way that rationalizes the development process of any software and management of data, respectively, to streamline the entire software development process and analysis. There is an emphasis on stimulating communication & collaboration between the involving parties and to make them into a stronger team that can deliver faster results with enriched quality.
How advantageous it is to implement DevOps and DataOps?
By adopting DevOps and DataOps in an organization, numerous benefits can be seen in the overall functioning. Let us see the advantages of incorporating DevOps and DataOps.
When DevOps is integrated for application development, the organization can experience improved transparency, better communication & collaboration within different teams with fast-track deployment schedules. The quality of utmost standards is ensured along with easy closure of errors. This eliminates the problems of deployment failures and rollbacks. The system is also prepared to deal with impromptu tasks. All this helps in reducing the overall costs & headcounts and allows faster mitigation of the live sites.
- DataOps DataOps revolutionizes the data processing by speeding up the working capabilities and improving resource returns. DataOps helps to address problems efficiently, enhances data security and improves the functioning through statistical process control. DataOps provides real-time data insights and progresses towards the goals for organizations
DevOps and DataOps must be handled very carefully to ensure smooth implementation of both these powerful entities. For that, a certain procedure must be followed to achieve the goal.
- Develop irreproachable communication between the responsible teams and devise a plan to foster collaboration between them.
- Divide large critical modules into smaller, manageable sections.
- Each such section should have an individual DevOps processing.
- Use available tools for seamless application deployment.
- Re-definition of the data storage & analytics infrastructure and incorporate cluster-based or redundant data storage method.
- Stay in-sync with the latest data analytics tactics for precise insights
- Practice microservices-based architecture & software to allow the interflow of structured & unstructured data. Tools like Map Reduce, Hive, Kafka, HDFS, and Spark can be used for this purpose of data amalgamation.
- Enforce built for purpose database engines to access and analyze huge datasets easily.
- Use supporting tools like ETL/ELT, data curation & cataloging tools, and log analyzers that can make the process agile, efficient, and help in collaborating with teams. Though there are no dedicated software tools available for conducting DevOps for DataOps, these frameworks and supporting tools are of great value to ensure agile-based project management.
In both cases, implementation requires tremendous team dedication to see success coming their way.
Implementing DevOPs and DataOps in your organization can take you a step forward in your journey. It will help you stay relevant with time and assist you in speedily managing the data. Strategies and approaches may shift with changing times and contexts. Still, the goal will always remain the same, i.e., attaining higher quality and high performing systems in all spheres of an organization. Integrating DevOps and DataOps in the organization can bring a digital transformation and productively transform the organization.