Sep
26
2018
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Instana raises $30M for its application performance monitoring service

Instana, an application performance monitoring (APM) service with a focus on modern containerized services, today announced that it has raised a $30 million Series C funding round. The round was led by Meritech Capital, with participation from existing investor Accel. This brings Instana’s total funding to $57 million.

The company, which counts the likes of Audi, Edmunds.com, Yahoo Japan and Franklin American Mortgage as its customers, considers itself an APM 3.0 player. It argues that its solution is far lighter than those of older players like New Relic and AppDynamics (which sold to Cisco hours before it was supposed to go public). Those solutions, the company says, weren’t built for modern software organizations (though I’m sure they would dispute that).

What really makes Instana stand out is its ability to automatically discover and monitor the ever-changing infrastructure that makes up a modern application, especially when it comes to running containerized microservices. The service automatically catalogs all of the endpoints that make up a service’s infrastructure, and then monitors them. It’s also worth noting that the company says that it can offer far more granular metrics that its competitors.

Instana says that its annual sales grew 600 percent over the course of the last year, something that surely attracted this new investment.

“Monitoring containerized microservice applications has become a critical requirement for today’s digital enterprises,” said Meritech Capital’s Alex Kurland. “Instana is packed with industry veterans who understand the APM industry, as well as the paradigm shifts now occurring in agile software development. Meritech is excited to partner with Instana as they continue to disrupt one of the largest and most important markets with their automated APM experience.”

The company plans to use the new funding to fulfill the demand for its service and expand its product line.

May
01
2018
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ScienceLogic release gives IT view across entire stack

It’s tough being part of IT Ops these days. Your company could be operating across public and private clouds, and in many cases, an internal datacenter too. Meanwhile your developers are generating more code ever faster. ScienceLogic wants to help with it latest release, ScienceLogic SL1.

As company CEO Dave Link sees, we are seeing this vast confluence of technology influences coming together very quickly. He says the goal with this release is nothing less than a comprehensive, full-stack view of how an application is behaving, and how the different pieces that make up and connect to that application could be affecting its performance.

“Every CIO wants to know the health of their mission critical business services and only way to see that is to see through the entire stack,” Link said.

Part of the problem of course is the sheer volume of information. As that increases, it becomes nearly impossible for humans, even the most highly skilled among us, to keep up and understand what particular element may be causing an application to misbehave.  That problem is exacerbated further by the speed at which developers are generating new code.

Murali Nemani, CMO at ScienceLogic, says that’s where artificial intelligence and machine learning come into play. “Part of the problem is that if businesses are moving at machine speed in terms of their capability to innovate, the big challenge is how do you get operations to keep up with what developers are creating,” Nemani asked.

The machine learning aspect of the platform enables companies to begin automating solutions for some of the more common problems, while directing the more unusual ones to humans on the operations team. They rely on the AI tools produced by others, rather than trying to develop that part of the solution themselves. “If an application is performing poorly, we can diagnose which part is the problem child, then feed this information to AI/ML engines like Google TensorFlow or IBM Watson and see pattern recognition. That’s the way we achieve machine speed,” Nemani explained.

Link says they do this by looking at the problem holistically and giving operations a full view of the application to track down the problem behavior and fix it. “We look at all the layers when we think of a service view: security, systems, network, OS, infrastructure then the application layer (database and application tier). We then contextualize all of those elements into one service view, so [the customer has] the most efficient view of what’s happening in real time,” Link said.

The product being announced publicly today has been early Beta up to now and will be generally available on July 25th.

Apr
21
2018
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Through luck and grit, Datadog is fusing the culture of developers and operations

There used to be two cultures in the enterprise around technology. On one side were software engineers, who built out the applications needed by employees to conduct the business of their companies. On the other side were sysadmins, who were territorially protective of their hardware domain — the servers, switches, and storage boxes needed to power all of that software. Many a great comedy routine has been made at the interface of those two cultures, but they remained divergent.

That is, until the cloud changed everything. Suddenly, there was increasing overlap in the skills required for software engineering and operations, as well as a greater need for collaboration between the two sides to effectively deploy applications. Yet, while these two halves eventually became one whole, the software monitoring tools used by them were often entirely separate.

New York City-based Datadog was designed to bring these two cultures together to create a more nimble and collaborative software and operations culture. Founded in 2010 by Olivier Pomel and Alexis Lê-Quôc, the product offers monitoring and analytics for cloud-based workflows, allowing ops team to track and analyze deployments and developers to instrument their applications. Pomel said that “the root of all of this collaboration is to make sure that everyone has the same understanding of the problem.”

The company has had dizzying success. Pomel declined to disclose precise numbers, but says the company had “north of $100 million” of recurring revenue in the past twelve months, and “we have been doubling that every year so far.” The company, headquartered in the New York Times Building in Times Square, employs more than 600 people across its various worldwide offices. The company has raised nearly $150 million of venture capital according to Crunchbase, and is perennially on banker’s short lists for strong IPO prospects.

The real story though is just how much luck and happenstance can help put wind in the sails of a company.

Pomel first met Lê-Quôc while an undergraduate in France. He was working on running the campus network, and helped to discover that Lê-Quôc had hacked the network. Lê-Quôc was eventually disconnected, and Pomel would migrate to IBM’s upstate New York offices after graduation. After IBM, he led technology at Wireless Generation, a K-12 startup, where he ran into Lê-Quôc again, who was heading up ops for the company. The two cultures of develops and ops was glaring at the startup, where “we had developers who hated operations” and there was much “finger-pointing.”

Putting aside any lingering grievances from their undergrad days, the two began to explore how they could ameliorate the cultural differences they witnessed between their respective teams. “Bringing dev and ops together is not a feature, it is core,” Pomel explained. At the same time, they noticed that companies were increasingly talking about building on Amazon Web Services, which in 2009, was still a relatively new concept. They incorporated Datadog in 2010 as a cloud-first monitoring solution, and launched general availability for the product in 2012.

Luck didn’t just bring the founders together twice, it also defined the currents of their market. Datadog was among the first cloud-native monitoring solutions, and the superlative success of cloud infrastructure in penetrating the enterprise the past few years has benefitted the company enormously. We had “exactly the right product at the right time,” Pomel said, and “a lot of it was luck.” He continued, “It’s healthy to recognize that not everything comes from your genius, because what works once doesn’t always work a second time.”

While startups have been a feature in New York for decades, enterprise infrastructure was in many ways in a dark age when the company launched, which made early fundraising difficult. “None of the West Coast investors were listening,” Pomel said, and “East Coast investors didn’t understand the infrastructure space well enough to take risks.” Even when he could get a West Coast VC to chat with him, they “thought it was a form of mental impairment to start an infrastructure startup in New York.”

Those fundraising difficulties ended up proving a boon for Datadog, because it forced the company to connect with customers much earlier and more often than it might have otherwise. Pomel said, “it forced us to spend all of our time with customers and people who were related to the problem” and ultimately, “it grounded us in the customer problem.” Pomel believes that the company’s early DNA of deeply listening to customers has allowed it to continue to outcompete its rivals on the West Coast.

More success is likely to come as companies continue to move their infrastructure onto the cloud. Datadog used to have a roughly even mix of private and public cloud business, and now the balance is moving increasingly toward the public side. Even large financial institutions, which have been reticent in transitioning their infrastructures, have now started to aggressively embrace cloud as the future of computing in the industry, according to Pomel.

Datadog intends to continue to add new modules to its core monitoring toolkit and expand its team. As the company has grown, so has the need to put in place more processes as parts of the company break. Quoting his co-founder, Pomel said the message to employees is “don’t mind the rattling sound — it is a spaceship, not an airliner” and “things are going to break and change, and it is normal.”

Much as Datadog has bridged the gap between developers and ops, Pomel hopes to continue to give back to the New York startup ecosystem by bridging the gap between technical startups and venture capital. He has made a series of angel investments into local emerging enterprise and data startups, including Generable, Seva, and Windmill. Hard work and a lot of luck is propelling Datadog into the top echelon of enterprise startups, pulling New York along with it.

Dec
01
2015
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AppDynamics Update Helps Track Business Transaction From User To Server

Virtual image of a Business man touching the process of triggering a software development process, which it connects the various systems globally through a single touch in a network and coding phase. In a week when a major retail website went down under the pressure of Cyber Monday, AppDynamics, a company that helps monitor apps and websites in order to prevent those types of outages (or at least understand why they happened and recover as quickly as possible) announced a major update today. The latest version helps identify those big problems that take down a website, but also see… Read More

Jul
08
2015
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Dynatrace Wants To Link Performance Monitoring With Customer Experience

Performance meter pinned to 100 percent. Dynatrace released the latest version of its application performance monitoring (APM) product today, which it hopes will shift the company from pure monitoring into the realm of customer experience. Although this is a major release with many new features, it centers on the Customer Experience Cockpit, which is effectively a dashboard that lets users see a User Satisfaction Rating along… Read More

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