Here at GigaOm we’re looking at how leading-edge technologies impact the enterprise, and what organizations can do to gear up for the future. Here’s a take from several of our analysts about what to watch for in enterprise IT and beyond, this coming year and in years to come.
From Kubernetesization to workforce automation, data center shrink and the rise of the architect, read on.
Andrew Brust, Big Data & Analytics
- “Kubernetesization” and Containerization of the Data Analytics Stack — both open source and commercial. To a large extent, this is one’s obvious. But it’s giving rise to something less so: a tendency to spin up clusters (be they for big data, data warehousing or machine learning) on a task-by-task basis. Call it extreme ephemeralism, if you’d like. It’s enabling a mentality of serverless everything. This architecture underlies the revamped Cloudera Data Platform, and it’s also being leveraged by Google for Spark on K8s on Cloud Data Proc. Ultimately, it’s enabling new workloads.
- Warehouse & Lake Converge, But in a Fragmented Fashion — We see this with SQL Server 2019 (its “Big Data Clusters” integrate Spark), Azure Synapse Analytics (which is the revamp of Azure SQL Data Warehouse and will also integrate Spark, as well as Azure Data Lake Store) and in the Redshift Federated Query and Parquet Export features AWS announced at re:Invent. Everyone is trying to bring warehouse and lake together, and make them operate like two different interfaces on a common data store. But everyone’s doing it their own way (in Microsoft’s case, they’re doing it two different ways). This divergence dulls the convergence that everyone’s aiming for.
- BI Goes Big Brand — Salesforce got Tableau, Google’s trying to close its acquisition of Looker and Microsoft’s got Power BI. It’s getting harder to be an independent BI provider. That’s probably why Qlik is building out its portfolio to be a comprehensive data analytics stack (including integration and data catalog) and not just BI.
- AI Tries to Get Its Act Together, and Has a Long Way to Go — New improvements announced for SageMaker, including AutoPilot, are steps in the right direction. Likewise many of the new features in Azure Machine Learning. But AI is still notebook-oriented and sloppy. It’s trying to get the DevOps religion and integrate with software development stacks overall, but it hasn’t fully happened yet. The need here is getting more acute by the week.
Stowe Boyd, Future of Work
- Workforce Automation — as distinct from back-office Robotic Process Automation (RPA), this is technology to automate rote, manual work, and maybe management work (like what middle managers do) in the not-too-distant future.
- Work Platforms. — From Uber/Lyft (which have had such an impact on the transportation sector), to myriad others. Expect the range of platforms to expand across industries, both consumer-facing and within business.
- Work Chat — Slack has led the charge in chat-based collaboration and communication but was mainly for techies and coastal elites. Now, Microsoft Teams is taking the simplicity and effectiveness of work chat mainstream.
JP Morgenthal, Digital Transformation & Modernization
- Geopolitical & Market Forces — The US is heading into an election year with a President surrounded by controversy and who continues to levy tariffs against trading partners. Key financial analysts are predicting the bull market is slowing and will have a profound effect on the markets. Potentially, many businesses will panic and pull resources and attention from digital transformations.
- Increased, Yet Misguided Use of Cloud/Mobile — The above will have an effect on consumption of cloud and mobile platforms and services. Many will forge forward with a cloud strategy still believing it will save them money, even though this has been thoroughly disproved time and again over the past decade. These failures will only further inhibit these businesses from being able to compete effectively.
- Technology-Driven Disruption — While the market will take a hit, money on the sidelines will continue to work: companies with products and offerings deemed disruptive will see big investments, as investors see the opportunity to unseat old-world monoliths. This will have a net effect of transforming the overall market landscape. Investments will be heavy in Artificial Intelligence, Digital Workers / Automation, consumer technologies, healthcare IT, and remote collaboration. Cloud will see benefits here as there will be a strong foundation for scaling in these areas.
- Quantum comes to Deep Learning — Quantum computing will also make major leaps in 2020 and we will start to see its impact on deep learning and forecasting.
Enrico Signoretti, Data Storage &Cloud Infrastructure
- Hybrid cloud is Still Considered as Another Silo, Alongside On-Prem & SaaS — Enterprise organizations want to manage their data in a better way and avoid silos. They still don’t know how (especially in the EU), nor do they understand the solutions available, their limitations, and their level of maturity.
- Storage Sees a Major Trend Towards Data Management — Connected to the above, and as data storage is increasingly commoditized, the differentiator comes from how you can manage the data saved in these storage systems.
- Investments Move Towards Edge Computing & Public Cloud, Shrinking Core Datacenters — This trend will stop sooner or later and we will see a balance emerge between the three, as data and applications become easier to move (for example based on Kubernetes plus adequate supporting infrastructure layers). It will take at least two years, but many vendors are already showing some very interesting developments.
Jon Collins, DevOps, Innovation & Governance
- DevOps Gets a Rebrand — No innovation philosophy lasts forever, and DevOps is showing its own weaknesses as a developer-centric idea centered on speed when enterprises need something balanced across stakeholder groups with value-driven innovation at its core. As the software development and operations industry matures, it too is looking for ways to meet the needs of organizations that are more complex and less able to change. Expect tooling to follow suit, encompassing broader stakeholders and an end-to-end view which better meets enterprise needs.
- Containerization Trumps Serverlessness — The industry has only had to wait 35 years for this one, as distributed systems finally have sufficiently powerful networking infrastructure to deliver Yourdon and Constantine (et al)’s notions of software modularity. Or, in layperson’s terms, application chunks can exist anywhere and still talk to each other. Containerization, based on Kubernetes or otherwise, is a popular manifestation of such chunking: the need for code modules to be self-contained and location-independent overrides any “please run on our serverless platform” exclusivity.
- Multi-Cloud Creates & Next Licensing Battle — The big cloud players have a fight on their hands and they know it. The competitor is unbranded access to commoditized compute and data storage resources, based on open and de facto standards, leveraging easy-to-shift chunks of innovation (see also: containers). Faced with the onslaught of write-once-run-anywhere, vendors have three weapons: differentiation through manageability (a good thing), data gravity (a moveable feast) and indeed, existing contracts and volume discounts.
- Architects & Policy-Setters Become the New Kingmakers — Even as organizations continue to pivot towards technology-based innovation at scale, just doing it becomes less and less of a differentiator (example: all automotive manufacturers will have driverless cars, then what?). As a result, attention in DevOps and elsewhere will turn away from effectiveness (doing the right thing) and back to efficiency (doing things right), manifested in terms of architectural, process and governance excellence.