Industry executives and experts share their predictions for 2019. Read them in this 11th annual VMblog.com series exclusive.
Contributed by Siddhartha Agarwal, group vice president, product management and strategy, Oracle Cloud Platform
10 Predictions For Developers in 2019
Developers should be burning with excitement about the
opportunities ahead in 2019, with technologies such as blockchain, chatbots,
and machine learning becoming mature enough for real-world projects. Instead,
many are worried about holding up against the pressure they face: deliver code
and functionality faster since business success is so directly tied to
technology innovations. For developers, 2019 will be defined by this tension
between seizing transformative new opportunities while coping with the pressure
to do more, with higher quality. Below are ten developer predictions related
to how those forces will play out in the year ahead.
1. Eight out of 10 custom
applications will include embedded intelligence as a first-class capability by
2020. So developers need to understand how data science works. Developers aren't going
to become data scientists -- one writes code, one thinks in
math and models. But devs will increasingly need to understand data science
methodologies, and to integrate data science models into their
workflow. Data makes software more intelligent, giving it the ability to
predict outcomes or anticipate user needs through machine learning. So
developers increasingly need a new level of partnership with data scientists to
make great work happen. Developers can expose the data scientists' models via
APIs, and embed them in domain-specific apps to really drive change. Consider a
retailer trying to intelligently decide which brick and mortar store to fulfill
e-commerce orders from. A data scientist can create the model that calculates
the optimal store from which to ship, so that the company ships the sweater
that was likely to sit on the shelf at a store in a warm location rather than
the one likely to get bought by an in-store shopper in frigid areas. A
developer could pull that kind of intelligence into a fulfillment app, and put
it in employees' hands to make the right decision.
2. Developers will need to partner with
a platform engineer, which will emerge as a key new role for cloud
native development. Think of this new platform engineer role as something like
the sys admin for the cloud. The platform engineer will marshal all
the resources needed to have a high performing cloud infrastructure on
which developers can build and deploy their cloud native
applications. Platform engineers will understand elements such as how to
employ kubernetes to orchestrate containers, and how to use tools like Istio and Envoy proxies to run a service mesh, which
is increasingly important for the complex service-to-service communication
of microservice applications. They'll also focus on ensuring security of
containers, and of communications between services, since both security and
availability are essential to using containers at scale within the
enterprise. Developers still get the benefits of the cloud -
they can develop and deploy in containers, and the cloud will scale
resources up and down to serve their apps based on demand. But it's a
platform engineer who will pull all that infrastructure together and have
it ready for developers to use.
3. To balance security
and performance needs, a hybrid model that falls between virtual machines and
containers will rise in popularity for deploying applications. The past year brought some
nasty security threats that should again remind developers that nothing else
matters if they get security wrong. In response, look for an application
deployment approach this coming year that delivers most of the performance and
efficiency of running in containers, but in a super lightweight virtual machine
that assures better security and isolation in multi-tenant environments. Kata Containers offer one promising implementation
of this idea, but similar concepts will arise elsewhere. Cloud service
providers will drive this innovation, but developers need to understand these
options and what performance tradeoffs and security gains they can bring.
4. The economics of serverless
become too compelling to ignore, driving serverless innovation on multiple
fronts. For
starters, an open standard for serverless will take clear shape, allowing
developers to embrace serverless like they have kubernetes, without the lock-in
risk many of today's serverless options have. We're not predicting exactly how
that will take shape - one leading platform, or several platforms with common,
standards-based building blocks? - but we'll see major progress by this time
next year. Second, serverless solutions will rapidly extend from today's
function-oriented solutions (Oracle Fn, AWS Lamba, Azure Functions) to other
business domains, such as cloud-first, serverless infrastructure for large-scale
data processing based around the Apache Spark, Flink, and Kafka ecosystems.
Like running big data on the cloud, the economics are just too compelling. Overall,
look for modern, open cloud architectures to rely heavily on serverless
the coming year as a way to abstract away additional platform dependencies,
accelerating open cloud development.
5. As bots proliferate,
developers turn to ‘assistants' to find the right bot for the job. Developers are going to
write lots of bots, with each one representing some kind of skill -- taking an
order, looking up inventory, or scheduling a delivery. But the user can't be
expected to hunt down the right bot for every job. Instead, users need an
intelligent interface - a digital assistant - that can look at each possible
bot, and recruit it as needed to get a task done. So if you go into your HR
app, you can tell a digital assistant that you want to file expense reports,
and that assistant will call upon the bot automation to execute your filing.
Conversational interfaces will keep growing in intelligence, and the
un-intelligent conversational interfaces will fade away. For certain use cases,
like order taking or inventory look ups mentioned earlier, intelligent
interfaces will provide more value than human interactions.
6. Developers choose their
clouds based on openness, and reject cloud lock in: Developers move to cloud
infrastructure so they can focus on creating, rather than on IT operations. So
when they pick a cloud to build on, they want a choice of languages, databases,
and compute shapes. And they want to be able to move workloads to any
cloud.They're increasingly wary of forked open source that limits the ability
to move among clouds, or the ability to adopt new innovations in the unforked
branches. That's why open source and open standards will take a center role as
developers choose clouds that avoid cloud lock-in.
7. Developers decide one cloud
isn't enough. While
the first wave of cloud often leaned on a single provider, the current
expansion will be a multi cloud strategy, especially with the plethora of SaaS
applications available, spreading workloads across multiple providers. The move
to cloud is a staged journey, and many on-premises workloads will remain for
years to come. Developers will demand the same tools and workflow across cloud
and on-premises deployments. An API that today pulls data from an on-prem HR
app might next year pull that same data from a software-as-a-service HR app,
routing the data to a customer application running on a public cloud.
8. Autonomous Databases will let developers speed their
applications to market scale: Developers want more than rapid
prototyping. They also want, when that prototype hits the mark, to get as many
people using their work, as fast as they can. That scale validates success --
and it lets developers get the feedback to make an application better. A
cloud-based, autonomous database makes both speed and scale possible. An
autonomous database means a developer doesn't have to think about
scaling, patching, provisioning, or tuning a database. Instead, they can just
focus on building their app, knowing they have a repository for their data that
will automatically scale to meet their needs. Developers gain productivity
since they can launch a high-powered database in minutes without help from a
DBA. Scale comes from the cloud, letting a business ramp up as much capacity as
needed, and to run it efficiently by letting the database tune and secure
itself.
9. Legacy, enterprise
applications jump to cloud-native development approaches: By now it's
clear that cloud native is the default choice for new, in-house development
projects. The harder part, though, is that 80%-plus of your tech stack that's
legacy and not cloud native. Look for new technologies and tactics that make it
possible to modernize and containerize legacy, enterprise apps, so you can deploy,
run and manage them in much the same way as cloud-native apps. Two specific
examples of bringing cloud-native approaches to enterprise apps: new operators
that can stand up WebLogic
domains in Kubernetes, and Helidon, a framework for building
Java applications as microservices to modernize Java monoliths. This trend is
good news for experienced developers, since it lets them build on the skills
they have and extend them into container-based, cloud-native environments.
10. If you're a developer in a
regulated industry, blockchain is coming your way. Developers working on
applications that draw data from external sources will soon be querying some of
that data from a blockchain ledger, especially if the applications are
used in regulated industries such as food and agriculture, pharmaceuticals, or
finance. Developers of cloud applications now can embed features that call
out to a blockchain cloud service, outside of their app. Using blockchain as a
cloud service means developers don't have to worry about the complexity of
implementing blockchain technology, such as assuring the performance and
scalability. Why blockchain, and not a database? Blockchain can deliver greater
trust and transparency around data coming from third parties such as
suppliers and shippers, and that trusted data can make it easier to comply with
regulations.
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About the Author
Siddhartha Agarwal is group vice president, product management and strategy, for Oracle
Cloud Platform
As Group VP, Product
Management and Strategy at Oracle, Siddhartha is responsible for division
strategy and revenue growth (organically & inorganically) for the Oracle
Cloud Platform (Platform-as-a-Service) and Fusion Middleware across all product
lines globally ($4.5B+ business). Prior to Oracle, he held several
leadership positions including WW Field Operations at Zend, VP of Sales at
Solidcore Systems and Regional VP of Sales at Totality. Siddhartha also founded
companies such as Teamscape (acquired by Peoplesoft) and Contractor Online as
VP of Engineering/CTO. He started his career at Oracle in development and
as Director, Development built Oracle's CRM eCommerce product, Internet Bill
Presentment and Payment.