Automation and orchestration of application workflows play a key role in operational data analytics projects.
Often underestimated, sometimes set aside in favor of tasks deemed to be of higher priority, the automation and orchestration of application workflows nevertheless play a key role in operational data analysis projects. Their mission? Guarantee a data flow continuous, end to end.
Recent European studies have shown that while 61%(1) of companies today place data analysis at the top of their priorities for technological investment, more than 50%(2) express difficulties in terms of their exploitation: problems access or location, poor quality of the data collected, excessive volume, variety of formats or operating in silos, the list is long. Minimizing the importance of data orchestration, especially at the start of a project, can indeed have critical consequences on the resulting business applications and services.
As the real cement of any IT project, the orchestration of workflows is therefore an essential foundation for the development of applications and data pipelines. This is a reflection that should in no case be carried out a posteriori, at the risk of hindering any attempt to develop applications, analyze data, machine learning or artificial intelligence. Ultimately, neglecting the central role of data orchestration could simply lead a project to its ruin, just like 85% of big data projects.
Importance of application and data flow orchestration
Faced with the need to aggregate, store, execute and analyze data to optimize their business, companies often turn to automation as a way to streamline the process. However, selecting automation tools without adopting a strategic approach, including the needs of IT operators (IT Ops), makes their operation more complex and their management more difficult.
In Part 4 of his “Data Engineering Essentials, Patterns and Best Practices” report, Gartner analyst Sumit Pal describes the importance of orchestrating and automate data pipelines: “Data must be moved, deconstructed and aggregated into the correct format before being consumed by downstream systems.” Orchestration thus connects the various sources and systems of a data pipeline to ensure a consistent flow of the latter, from start to finish.
When done well, orchestration therefore ensures that the different stages of the data or application flow take place in the right order and at the right time, in favor of the business service. This requires the implementation of platforms offering a single point of control and scalable orchestration, driven by API. By reducing the complexity of processes and automating them from end to end, they make it possible to take advantage of the technology and data available and to integrate them with the latest business applications, to provide the company with information with high added value.
Features at the service of performance
While early implementation of application and data workload orchestration is essential, certain features are also essential for it to work:
- End-to-end visualization: Visibility is one of the most critical attributes of a robust platform. It should provide a comprehensive view of critical applications, data sources, and systems of record, from mainframe to cloud. Being able to view workloads end-to-end improves the identification and remediation of current and potential issues.
- Hybrid and cloud integration: As the use of private, public, and hybrid cloud environments grows, the need for a platform that can operate seamlessly becomes critical. It should take advantage of the flexibility and scalability of cloud ecosystems, provide end-to-end visibility of workloads in hybrid environments, and provide the same high level of automation regardless of the cloud technology used.
- SLA management: Good service level agreement (SLA) management features enable proactive workflow planning and troubleshooting, and help avoid delays in business services. The ability to determine the impact of potential delays or errors on SLAs provides better business insights. The result: more informed decisions, less risk of SLA violations for critical applications and, ultimately, less disruption for the company.
- Managed File Transfer Features: Business operations involve moving files between multiple applications and systems of record. However, using separate products to manage these transfers as well as application workloads requires scripting and manual intervention, creating unnecessary risks, including potential violation of SLAs. A good application workload orchestration platform integrates file transfers with related workloads, streamlining the entire process.
- Security and Governance: Workflows, by definition, manage business-critical services. It is therefore essential that everyone accesses the data that is authorized to them and handles it in accordance with the company’s business practices. A robust and granular security model ensures the controls required to secure access to the appropriate resources and functions, according to defined roles and users. Comprehensive auditing, reporting, and version control should highlight any information necessary to track and analyze events of interest, while data codification and standardization ensures greater compliance with operational practices and corporate security guidelines. company.
- DevOps support: Ideally, application workload orchestration should be integrated into the development process as early as possible. To do this, Dev and Ops must work together as the development phase progresses, in a jobs-as-code approach. Automation API features make workloads versionable, testable, and maintainable. Each person involved can therefore contribute to the definition, planning, management and monitoring of application flows in production. As a result, IT departments can reduce costs and improve the quality of their applications by catching defects and bugs earlier in the development cycle.
Critical to business success, implementing an application and data flow orchestration platform can not only streamline data pipelines, but also help meet or improve SLAs, meet long-term goals and improve overall business results.
(1) European Future Enterprise Resilience Survey 2021
(2) IDC European Software Survey 2021
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The orchestration of application workflows, the cement of a winning data project
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