All Posts By

Arushi Pandey

Fragmented DevOps = Minimal Value | Blog

By | Automation/RPA/AI, Blog

Enterprises are increasingly embracing DevOps to enhance their business performance by accelerating their software time-to-market. In principle, DevOps covers the entire spectrum of Software Development Life Cycle, SDLC, activities from design through operation. But, in practice, only ~ 20 percent of enterprises are leveraging DevOps end-to-end, according to our recent research, DevOps Services PEAK Matrix™ Assessment and Market Trends 2019 – Siloed DevOps is No DevOps!

That means the remaining ~ 80 percent that are taking a siloed approach to DevOps are missing out on the many types of values it can deliver.

Types of DevOps fragmentation

Instead of adopting DevOps in its intended end-to-end fashion, many enterprises in different verticals and at different stages of maturity are tailoring it to focus on siloed, distinct portions of the SDLC. The most common types of fragmentation are: 1) Apps DevOps, applying DevOps principles only across the application development cycle; 2) Test Ops, using DevOps principles in testing; and 3) Infra Ops, applying DevOps principles only to infrastructure.

Why fragmentation delivers minimal value

Pocketed adoption makes it tough to realize the full value that DevOps can deliver. The primary reason is bottlenecks. First, workflow throughout the SDLC is impeded when DevOps principles and automation are only applied to certain phases of it. Second, lack of end-to-end adoption makes it more difficult for enterprises to gain a full view of their applications portfolio, spot bottlenecks, incorporate stakeholder feedback in real-time, and make the entire process more efficient.

Additionally, when DevOps is used in a siloed manner, it focuses primarily on increasing the technical efficiency of processes. This means that DevOps’ ability to support the enterprise’s broader business-oriented objectives is severely restricted.

Finally, fragmented DevOps adoption creates a disintegrated culture in which teams work independently of each other, in turn leading to further conflicts, dependencies, and stretched timelines. All this, of course, defeats DevOps’ main purpose.

Moving to end-to-end DevOps adoption

To successfully adopt DevOps end-to-end, enterprises should place automation, culture, and infrastructure at the heart of their strategy.

  • Automation: Automating various elements of the SDLC is extremely beneficial; doing so helps reduce implementation timelines and increase team productivity by standardizing processes and diminishing the scope of errors
  • Culture: A collaborative culture is essential to a successful DevOps implementation as it involves the development, operations, and business teams working together in an iterative fashion to achieve cross-team and business-oriented KPIs
  • Infrastructure: Increasing adoption of cloud-native technologies like as infra-as-code, microservices, serverless, and containers helps maintain configuration consistency in deployment, eventually leads to an increase in developer productivity, and saves on cloud computing costs.

DevOps has the ability to deliver significant value to enterprises. But implementing it in a siloed manner quickly dilutes a lot of that potential value. To realize all DevOps’ benefits, enterprises should implement it end-to-end, invest in automation, robust and modular infrastructure, and tools and technologies to ensure agility, and develop a culture that helps them improve cross-team collaboration.

What has been your experience in your DevOps adoption journey? Please share with us at [email protected] and [email protected].

Spotlight on Salesforce’s Acquisition of Tableau | Blog

By | Blog, Mergers & Acquisitions

On June 10, 2019, Salesforce announced an agreement to acquire Tableau, a leading interactive data visualization company, for US$15.7 billion in an all-stock deal. Here’s our take on it.

Strategic Intent behind the Deal

The announcement is a masterful move to aid Salesforce’s hyper growth agenda to become a US$28 billion company in three years’ time. In the past 15 months, Salesforce has accelerated the data pivot through its acquisitions of Mulesoft in March 2018 and now Tableau, for a combined value of $22.2 billion.

Given its ambitious topline growth goals, Salesforce has hedged its bet against a pure cloud play. Tableau, which is not a cloud company, runs most of its products on-premise, with over one-third deployments in the cloud. However, last year, Tableau announced that its products will also be available on hyperscalers’ cloud platforms (AWS, Microsoft Azure, and GCP.) Addressing the ubiquity of data in a modern enterprise and recognizing the transition in software consumption pattern, Salesforce is taking an “anytime, anywhere” analytics approach to cater to enterprise’s hybrid cloud-first mandate.

In addition, Tableau’s strong performance against rivals including IBM Cognos, MicroStrategy, Oracle BI, and QlikView makes a strong case for the acquisition, given Salesforce’s big bet on its Customer 360 initiative and its broader foray into empowering clients with data analytics and visualization capabilities.

Enhancing the Data Analytics and Experience Pivot

Salesforce, a veteran in the CRM space, is repositioning itself as a digital experience (DX) platform, wherein it intends to become a one-stop, end-to-end solution for enterprises’ DX needs. It has been making strategic acquisitions over the years to plug in the gaps in its DX platform portfolio to achieve this goal.

SFDC Acquisition blog DX image

Because Tableau and Salesforce’s in-house analytics tool, Einstein Analytics, can easily interoperate, the company will be able to sell a well-packaged data analytics offering. Tableau’s niche capabilities in data analytics will not only deliver an improved data management solution but will also help enterprises form data-intensive strategies and optimize the overall stakeholder experience. And, the acquisition gives Salesforce new up- and cross-sell opportunities, as enterprises will be able to purchase CRM and business intelligence (BI) capabilities from a single vendor.

Gaining a Full View of Enterprise Data

Looking at the timeline of Salesforce’s acquisitions, we see a strategic shift from targeting digital marketing and commerce space toward enhancing enterprise data lifecycle management. Since 2018, Salesforce’s top deals have been to expand its coverage in the data and analytics space. Undoubtedly, the move has given Salesforce a shot in the arm when it comes to showcasing its capabilities across the data management value chain. Tableau sits atop of its acquisitions, plugging in multiple outside data sources and offering an easy to use UI for data visualization.

SFDC Acquisition blog CRM image

Indeed, Salesforce’s acquisition of Tableau is a strategic next step after its 2018 acquisition of MuleSoft. While Salesforce leveraged Mulesoft to create a “Salesforce Integration Cloud” that allows different cloud applications to connect via APIs, Tableau can help it gain deeper insights in this data, in turn driving enterprises toward data-driven decision making.

Data Orchestration Meets Cognitive

We give a thumbs up to this deal, particularly for what it means to the market going forward. Why?

The move fits well with Salesforce’s agenda to move into machine learning-driven analytics. Essentially, it will now have a strong BI tool, underpinned by AI, that will democratize enterprise access to next-generation data modeling and analytics capabilities.  A Tableau-integrated Salesforce Einstein Analytics offering should be able to deliver an intelligent, intuitive analytics and data visualization platform that leverages enterprise-wide data to help enterprise customers, employees, and partners with well-curated insights.