After a whirlwind year full of fast pivots we expect to see a lot of changes in how enterprises leverage technology to drive business outcomes. We’ve compiled our predictions for next year’s biggest enterprise tech trends within digital transformation, cloud-native, edge computing, security, and automation.
1. Remote-First Virtual Business
With COVID-19 forcing the proliferation of remote work, most businesses implemented or strengthened virtual work capabilities in 2020. However, few companies can say that have embraced a truly remote-first approach.
This will change in 2021. Businesses will shift from a reactionary approach towards remote work to a focus on how to do it scalably, efficiently, and securely across the organization.
2. Optimized Costs to Enable Growth
Budgets will remain tight in 2021. CIOs will need to optimize costs and channel those saving into projects that focus on growth opportunities. This requires a balanced portfolio of harvest and investment projects. Applications and platforms must become nimble to keep pace with business and the adoption of modern architecture techniques will be critical for success. CIOs will focus more deeply on IT financial transparency to understand where each dollar is spent.
3. Re-envisioned Digital Experiences
Now that business transactions are predominantly digital, every customer, patient, provider, and seller interaction has changed. Businesses are fast-tracking innovation to improve these experiences through the use of smart technology. Having more fully realized the value of digital user experiences, organizations will renew their focus on modernizing applications and creating cloud-native apps that drive digital interactions and transactions.
4. The Downfall of the Cloud Computing Iron Curtain
Historically, the major public cloud providers have walled off their clouds and have not played nice with others. Having a true, multi-cloud presence usually requires custom work. As enterprises trend towards multi-cloud and hybrid-cloud environments, the pressure is mounting on cloud providers to offer turnkey solutions for connecting competing cloud environments.
As cloud providers build these bridges to each other, it will become increasingly simple and affordable for organizations to leverage the best bits of each cloud provider, as well as create additional layers of resilience and availability. Hybrid cloud technologies such as Google’s Anthos also allow enterprises with existing data centers to leverage the hardware they already own and keep sensitive data on-prem, while still integrating with their cloud infrastructure. These trends will lead to easier adoption for those that have been unable to do so thus far, as well as more complete solutions to particular business problems that require pulling from the toolchains of multiple providers to best solve the problem.
5. Data Liberation Proliferates
In 2020 we saw an ongoing movement away from structured data warehouses to a data lake-focused approach to collection and retention of massive data volumes. Retaining ingested/collected data in its original form opens up opportunities for event sourcing and just-in-time open-ended data analytics and ML use cases. Such use cases are supported by the widening adoption of scalable compute frameworks such as Apache Spark. These frameworks go beyond the capabilities of what is traditionally served by, for example, Hadoop MapReduce-centric data processing.
Many organizations are still early in the process of adopting Big Data strategies and dealing with its consequences. Collecting and retaining valuable data is served well by avoiding up-front assumptions about what use cases this data will serve. Data lakes allow for a variety of data formats to be represented, thus avoiding dilution of the source data to a currently perceived canonical format. Modern massively scalable compute frameworks can now take the role of manipulating raw source data in a manner suitable for specific use cases as they are discovered and implemented.
6. Enterprise Integration Redux
As digital scalability became paramount, enterprises in 2020 made significant investments to rebuild the beating heart of the IT application and service portfolio—enterprise integrations and supporting workloads. While the cloud-native app modernization revolution started years back by targeting core systems and applications to deliver efficiency, speed, agility, and ultimately a flawless customer experience, today’s focus has shifted towards building a robust integration foundation that is primed to serve the next 10-15 years of digital demands.
While most organizations understand the complexity of integration topologies inside their organization, many enterprises have only begun to draw the connection between these complex integrations and the bottlenecks that they can create from a digital standpoint. As organizations look to double down in this arena, expect to see innovation continue to spin up or grow stronger in this domain. Technologies like Kafka, Spark, and Airflow highlight the tools that enterprises will lean on heavily in this herculean effort to modernize how integrations get done.
7. Pick-a-Service, Pick-an-Environment Model Finally Takes Hold
One of the exciting patterns in the early days of cloud was the promise of being able to decouple the thing I’m trying to deploy from the place I’m trying to deploy it. Approaches to cloud migrations and modernizing apps are now decomposing into microservices, where the place I’m deploying to is now totally new, such as a container and not just a VM. And the thing we’re trying to deploy is no longer one JAR file—it’s now 30 JAR files. This has highlighted the limitations of the traditional approach, as if we didn’t know them already. And yet it hasn’t been until very recently where we’ve seen tools like Harness.io, Azure DevOps, VMware Tanzu, and Amazon Code tools embrace this pattern and build these products and services around this ideal of decoupled apps/app locations.
While the shift seems subtle, this paradigm and pattern allows organizations to templatize not only the process of building apps and services, but also templatize the process of deploying the application or services without completely unique CI/CD pipelines. These developments simplify modern application development and DevOps processes, especially when done at scale, leading to greater speed and efficiency for 2021 projects.
8. Containers and Serverless – Not an Either/or Choice
In 2020 we continued to see containers and serverless prove themselves as beneficial enterprise technologies because they lower costs (on-demand compute), scale (spin up / spin down), and can make teams more efficient (automated build and release). We also saw customers faced with the challenge of wanting to embrace serverless, full-stop, with the reality that the large majority of enterprise applications can’t run entirely on a serverless architecture. What organizations tend to find is that technologies such as serverless can be paired with either container-based application components or even traditional VM-based components— especially common when organizations are in process of modernizing systems.
In a distributed world of enterprise computing, the dichotomy of choice between either containers or serverless holistically will continue to slowly melt away. We expect this mix and match composability of modern systems and the abstracted platforms they sit on to grow in popularity and adoption in 2021.
9. Buildpacks – A Cloud-Native Developer’s Favorite Abstraction
As container-based application and service deployments on top of Kubernetes continued to grow in 2020, we began to see the pendulum start to swing back away from finer grain container composition control needs within the developer workflow to an outsourced approach that leverages cloud-native buildpacks to create the container artifacts that are ultimately deployed. This approach allows developers to reduce the time needed to handcraft the containers where apps and services run. The growing popularity of buildpacks is visible across enterprises looking to build and run containers at scale, as well as in ISV and the open-source community.
As we move into 2021, expect to see greater adoption of cloud-native buildpacks. Their outsourced efficiency coupled with the simplification they provide in situations where common vulnerabilities require updated containers to be deployed is simply unmatched today.
10. Greater Proliferation and Expansion of ARM Devices at the Edge
With the increased levels of advancement and innovation being made across a wide range of ARM-based technologies, including SoC (system on chip) design architecture, the variety and power of edge endpoint devices will enable application workloads previously not thought possible. Couple this with the huge community investments for every major operating system and popular open-source projects, 5G connectivity, and software-friendly hardware designs, and we get a new generation of use cases for the enterprise at the device edge.
11. Increase in FPGA Solutions for Edge Computing
Field-programmable gate array (FPGA) was originally developed as a middle-ground solution that provided a compromise between performance gains of fixed-purpose, application-specific integrated circuit (ASIC) hardware architecture and the general-purpose nature of CPU architectures. With modern optimizations, SoC FPGA can now provide a best of class cost-to-performance balance for certain edge computing use cases. One example would be data cleansing, filtering, and transformation. In a case where terabytes of sensing data are generated each day, SoC FPGA can be programmed to resample the stream of data, filter out the unimportant data, perform data cleansing, and minimize the effective size of the data set, in some cases down to 1-2% of the original data volume, without imposing any latency and maintain the real-time nature of the data itself.
12. Kubernetes will Continue to be the Orchestrator of Choice at the Edge
Containerization has proven to be the optimal way to package and distribute applications at the edge, and Kubernetes is the preferred technology to automate deployment, scaling, and management of those containerized applications. What was once a technology associated with larger data centers and hyper-scalers, Kubernetes will continue to expand its footprint at the edge in industries such as retail, healthcare, and transportation. Streamlined, lightweight distributions including k3s, a certified Kubernetes distribution originally built by Rancher Labs for IoT and edge computing, MicroK8s by Canonical (the company behind the popular Ubuntu Linux distribution), and the more recent k0s project developed by the folks at Mirantis, make running Kubernetes reliably at the edge on smaller, more resource-constrained compute nodes relatively simple.
13. Differentiated Strategies for Monitoring at the Edge
It will be important for vendors and their customer organizations to approach monitoring at the edge differently than they have in the data center or in the cloud. Because of the rather volatile nature of edge technologies, organizations should shift from solely monitoring the health of devices or the applications they run to also monitoring the digital experience of their users. This user-centric approach to monitoring takes into consideration all of the components that can impact user or customer experience while avoiding the blind spots that often lie between infrastructure and the user.
14. Analytics at the Edge will Become Standard
Up until now, there were two flawed approaches to handling the huge influx of data and applying analytics to that data. One approach was to perform analytics at the core (on-premises or in the cloud); however, sending data back and forth was mired by challenges associated with latency, privacy, connectivity, power consumption, and cost. The other approach was to perform a type of pre-processing of the data via near-edge technologies or gateways. This, however, also had its share of challenges due to the increased complexity of data solutions, especially in use cases with a high-volume of events or limited connectivity. Now, AI/ML-optimized hardware, container-packaged analytics applications, frameworks such as TensorFlow Lite and tinyML, and open standards such as the Open Neural Network Exchange (ONNX) encouraging machine learning interoperability, are enabling on-device machine learning and data analytics at the edge a reality.
15. More Attacks are Coming
As we’ve seen over the last few weeks of 2020 with the attacks on FireEye and SolarWinds, cyber attackers are waging digital warfare against organizations. As cyber attackers strengthen their arsenal of tools and approaches, we can expect this trend to continue into 2021.
As risks and consequences of successful attacks are brought front and center, organizations will become increasingly focused on layering security across every level of technology.
16. Remote Workers are Not Immune
Most companies did a good job of quickly transitioning into remote work in early 2020, but security was often not placed as a top priority. The seeds of poor security process planning could be reaped in 2021 with increased targeting of remote workers, especially those using devices lacking basic protections and without proper security education.
17. Data Protection Investments will Rise
Data Protection will continue to grow, especially cyber recovery solutions. The ransomware reality will force enterprises to invest in these additional solutions as business continuity measures. Data security will increasingly be seen as an essential investment, especially as technology like IoT reaches further into the enterprise.
18. Increasingly Relentless Automation
Organizations can no longer tolerate prolonged and tedious manual processes. They eat budget unnecessarily, require too much time, and leave wide room for human error. Automating redundant tasks and providing self-service portals creates efficiencies, empowers employees, lowers costs, and improves customer satisfaction. Next year we’ll see an increased examination of when and where automation can streamline processes.
19. Creation of Cross-functional Automation Teams
Over the past few years organizations have started to break out of the pocketed approach to automation, building in strategy and rigor.
In 2021 we’ll continue to see a formal approach develop, including organizational restructuring with cross-functional automation teams. Much like cloud communities of excellence, these automation teams will represent different areas of the business and IT team to ensure automation is not only done, but done right.
20. Advancements Towards Automated Governance and Security
Automation has long managed desired state configurations on virtual machines. Driven by increasing security threats, in 2021 automation will extend to include adherence to governance and security configurations.
Organizations will continue to realize the power of automation to provide greater efficiencies and will be willing to do the work of building in security on top.
21. Moving Towards AIOps
Monitoring automation has proven to be tremendously value to enterprise organizations. Next year, it will continue to grow its intelligence and see traction in working on behalf of IT operations teams.
The combination of AI and automation to identify and resolve performance issues and or prevent adverse events is a no-brainer for organizations ready to take this leap.