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Observability and AIOps: The Perfect Combination for Dynamic Environments

IT teams live in dynamic environments and continuous integration/continuous delivery has been in high demand. In the dynamic environment, DevOps and underlying technologies such as containers and microservices, continue to grow more dynamic, and complex. Now, just like DevOps, observability has become a part of the software development life cycle.

With basic monitoring techniques, ITOps and DevOps teams lack the visibility to support the explosive growth in data volumes that arise in these modern environments. And, that’s also because they cannot scale with manual processes. Traditional monitoring systems focused on capturing, storing, and presenting data generated by underlying IT systems. Human operators were responsible for analyzing the resulting data sets and making necessary decisions, making the IT processes human-dependent.

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Testing Robin, the RPA Programming Language Using Itself

Software testing in most software houses involves testing web/mobile apps, on-premise, in the cloud or hybrid installations, desktop apps, embedded software/hardware platforms and the like. What about testing a programming language though? How do you approach such a task?

Of course, given the fact there are many popular, tried-and-tested languages out there, there are a plethora of possible approaches but we will attempt to follow a different one (approach) and provide an RPA domain-specific example.

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All You Need to Know About Building Your RPA CoE

When we think of automation, we think of deploying bots to make a company’s vision come true, and empower them in increasing overall business value. When it comes to RPA in banks or insurance companies, it is far more effective to deploy a software bot that performs repetitive tasks, at scale, round the clock with near-perfect accuracy. Scores of enterprises see RPA as the key to assist them in resolving challenges associated with cost and operational scalability.

To reach this objective effectively, we recommend and assist clients towards building an RPA Centre of Excellence (CoE), which helps in embedding automation effectively across the organization and dispense knowledge base as well as resources for future deployments.

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Bringing RPA to Its Next Frontier: The Cloud

The next RPA frontier

Introduction

The adoption of robotic process automation (RPA) continues to accelerate. In fact, according to Gartner,  it’s the fastest-growing segment of the global enterprise software market, with revenue increasing 63.1% to $846 million in 2018. Gartner forecasts RPA software revenue will reach $1.3 billion in 2019.

Despite these extraordinary figures, we have not yet reached the precipice of where this transformative technology will take global enterprise and society as a whole.