5 predictions for Kubernetes in 2020
How do you track a wildly popular project like Kubernetes?
How do you figure out where it’s going? If you are contributing to the project
or participating in Special Interest Groups (SIGs), you might gain insight by
osmosis, but for those of you with day jobs that don’t include contributing to
Kubernetes, you might like a little help reading the tea leaves. With a
fast-moving project like Kubernetes, the end of the year is an excellent time
to take a look at the past year to gain insight into the next one.
This year, Kubernetes made a lot of progress. Aside from
inspecting code, documentation, and meeting notes, another good source is blog
entries. To gain some insights, I took a look at the top ten Kubernetes
articles on Opensource.com. These articles give us insight into what topics
people are interested in reading, but just as importantly, what articles people
are interested in writing. Let’s dig in!
(Get the full list of top 10 Kubernetes articles from 2019
at the end.)
First, I would point out that five of these articles tackle
the expansion of workloads and where they can run. This expansion of workloads
includes data science, PostgreSQL, InfluxDB, and Grafana (as a workload, not
just to monitor the cluster itself) and Edge. Historically, Kubernetes and
containers in general have mostly run on top of virtual machines, especially
when run on infrastructure provided by cloud providers. With this interest in
Kubernetes at the edge, it’s another sign that end users are genuinely
interested in Kubernetes on bare metal (see also Kubernetes on metal with
OpenShift).
Next, there seems to be a lot of hunger for operational
knowledge and best practices with Kubernetes. From Kubernetes Operators, to
Kubernetes Controllers, from Secrets to ConfigMaps, developers and operators
alike are looking for best practices and ways to simplify workload deployment
and management. Often we get caught up in the actual configuration example, or
how people do it, and don’t take a step back to realize that all of these fall
into the bucket of how to operationalize the deployment of applications (not
how to install or run Kubernetes itself).
Finally, people seem to be really interested in getting
started. In fact, there is so much information on how to build Kubernetes that
it intimidates people and gets them down the wrong path. A couple of the top
articles focus on why you should learn to run applications on Kubernetes
instead of concentrating on installing it. Like best practices, people often
don’t take a step back to analyze where they should invest their time when
getting started. I have always advocated for, where possible, spending limited
time and money on using technology instead of building it.
5 predictions for Kubernetes in 2020
So, looking back at those themes from 2019, what does this
tell us about where 2020 is going? Well, combining insight from these articles
with my own broad purview, I want to share my thoughts for 2020 and beyond:
Expansion of workloads. I would keep my eye on
high-performance computing, AI/ML, and stateful workloads using Operators.
More concrete best practices, especially around mature
standards like PCI, HIPAA, NIST, etc.
Increased security around rootless and higher security
runtimes classes (like gVisor, Kata Containers, etc.)
Better standardization on Kubernetes manifests as the core
artifact for deployment in development and sharing applications between
developers. Things like podman generate kube, podman play kube, and all in one
Kubernetes environments like CodeReady Containers (CRC)
An ever-wider ecosystem of network, storage and specialized
hardware (GPUs, etc.) vendors creating best of breed solutions for Kubernetes
(in free software, we believe that open ecosystems are better than vertically
integrated solutions)[Source]-How do you track a wildly popular project like
Kubernetes? How do you figure out where it’s going? If you are contributing to
the project or participating in Special Interest Groups (SIGs), you might gain
insight by osmosis, but for those of you with day jobs that don’t include
contributing to Kubernetes, you might like a little help reading the tea
leaves. With a fast-moving project like Kubernetes, the end of the year is an
excellent time to take a look at the past year to gain insight into the next
one.
More on Kubernetes
What is Kubernetes?
Test drive OpenShift hands-on
Watch: An introduction to Kubernetes
eBook: Getting started with Kubernetes
How to explain Kubernetes in plain terms
Latest Kubernetes articles
This year, Kubernetes made a lot of progress. Aside from
inspecting code, documentation, and meeting notes, another good source is blog
entries. To gain some insights, I took a look at the top ten Kubernetes
articles on Opensource.com. These articles give us insight into what topics
people are interested in reading, but just as importantly, what articles people
are interested in writing. Let’s dig in!
(Get the full list of top 10 Kubernetes articles from 2019
at the end.)
First, I would point out that five of these articles tackle
the expansion of workloads and where they can run. This expansion of workloads
includes data science, PostgreSQL, InfluxDB, and Grafana (as a workload, not
just to monitor the cluster itself) and Edge. Historically, Kubernetes and
containers in general have mostly run on top of virtual machines, especially
when run on infrastructure provided by cloud providers. With this interest in
Kubernetes at the edge, it’s another sign that end users are genuinely
interested in Kubernetes on bare metal (see also Kubernetes on metal with
OpenShift).
Next, there seems to be a lot of hunger for operational
knowledge and best practices with Kubernetes. From Kubernetes Operators, to
Kubernetes Controllers, from Secrets to ConfigMaps, developers and operators
alike are looking for best practices and ways to simplify workload deployment
and management. Often we get caught up in the actual configuration example, or
how people do it, and don’t take a step back to realize that all of these fall
into the bucket of how to operationalize the deployment of applications (not
how to install or run Kubernetes itself).
Finally, people seem to be really interested in getting started.
In fact, there is so much information on how to build Kubernetes that it
intimidates people and gets them down the wrong path. A couple of the top
articles focus on why you should learn to run applications on Kubernetes
instead of concentrating on installing it. Like best practices, people often
don’t take a step back to analyze where they should invest their time when
getting started. I have always advocated for, where possible, spending limited
time and money on using technology instead of building it.
5 predictions for Kubernetes in 2020
So, looking back at those themes from 2019, what does this
tell us about where 2020 is going? Well, combining insight from these articles
with my own broad purview, I want to share my thoughts for 2020 and beyond:
Expansion of workloads. I would keep my eye on
high-performance computing, AI/ML, and stateful workloads using Operators.
More concrete best practices, especially around mature
standards like PCI, HIPAA, NIST, etc.
Increased security around rootless and higher security
runtimes classes (like gVisor, Kata Containers, etc.)
Better standardization on Kubernetes manifests as the core
artifact for deployment in development and sharing applications between
developers. Things like podman generate kube, podman play kube, and all in one
Kubernetes environments like CodeReady Containers (CRC)
An ever-wider ecosystem of network, storage and specialized
hardware (GPUs, etc.) vendors creating best of breed solutions for Kubernetes
(in free software, we believe that open ecosystems are better than vertically
integrated solutions)
Basic & Advanced Kubernetes Certification using cloud computing, AWS,
Docker etc. in Mumbai. Advanced Containers Domain is used for 25 hours
Kubernetes Training.
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