The deep observability market has gained a lot of attention over the past 18 months and presents a clear opportunity for the channel if it can provide customers with products and services.
The technology underpins digital transformations, cloud migrations and is increasingly helping improve security around customer adoption of artificial intelligence (AI), but those selling the technology need to be aware of the pressures being faced by those seeking help.
“In the rush to implement digital transformation, CIOs typically are looking to increase the efficiency and the effectiveness of their application stack,” said Shane Buckley, CEO of Gigamon.
He added that the approach has changed over the years, from packet to flow-based to metadata, but the pressures have increased and the need for partners to educate customers remains.
“The pressure is growing exponentially faster than the budget. That makes for a very interesting conversation with customers, so doing more with less is important. One of the biggest trends is about more efficient tooling, with a lot of organisations looking to remove layers of tools,” he said.
That ambition to consolidate technology is combined with a number of customers that are using visibility tools that are generating thousands of alerts but failing to provide the results they are looking for.
“Improving the signal-to-noise ratio in such a way that you’re driving the customer to precisely the issue that is important for them, and they can pull that needle out of a whole field of haystacks. That power is what helps people understand the value of deep observability, because otherwise, if you’re just logging everything in the technology terms, it’s like you have to look at every piece of straw in the haystack to figure out if it’s good or bad. And guess what? You’re never going to do that,” he said.
“We take a lot of the noise of the junk out of the network, so that you’re just getting high-fidelity telemetry into your tool stack. That makes the tool stack lower. Cost converges much faster, so the overall health network goes up.”
Buckley joined Gigamon around seven years ago. In his first year at the helm, the business embarked on a channel-first go-to-market model that has remained at the heart of its approach.
“Channel-first is a programme we’ve implemented right across the entire organisation. We put the customer at the centre of the company, and our channel partners are the first port of discussion and engagement from a company perspective. That’s enabled us to form very deep and meaningful partnerships with some of the leading channel partners worldwide,” he said.
One of the current initiatives is the “power of three”, where Gigamon works with an ecosystem partner and a channel player.
Jon Kane, senior sales director for EMEA channels and alliances at Gigamon, has been leading efforts to put that approach into practice with partners.
“So far this year, the target has always been to make sure the power of three is absolutely crucial. We’re working very closely with some of those other ecosystem vendors. Each region is different, but if we look at where we’ve had success, particularly in the UK, working with some of these key vendors, where we can talk about the fact that our product will do this, but working in conjunction with another product and with a partner selling it is absolutely vital,” he said.
“These are opportunities where partners are bringing us into brand new end users. That’s already an increase year on year,” he added.
Buckley said the market for deep observability remains a strong one, adding that it is expecting continued opportunities for its partners throughout the rest of the year.
“I remain very confident in our opportunities as a company in 2025, here in the UK and across the world. I think we are at the right place in the perfect storm,” he said.
“Our channel partners [can share] a number of important messages. One, you can reduce costs overall by deploying, more broadly, a Gigamon fabric. Two, you can improve the security posture even as you reduce cost. And three, you can start deploying AI technology in a way that is deterministic, and you can understand what it’s doing inside your infrastructure.”