Want to know how much website downtime costs, and the impact it can have on your business?
Find out everything you need to know in our new uptime monitoring whitepaper 2021



Instagram, the photo-sharing app purchased by Facebook last year for $715m (£455m) – somewhat lower than the $1bn it had originally bid following a sharp fall in Facebook shares – is rumoured to being unveiling a video sharing service later this week at an event on Thursday to be hosted by the social media giant.
Rumours of a video service first surfaced a few weeks ago when Matthew Keys, a well known technology blogger, claimed that Instagram would soon allow 5-10 second video clips to be added. It’s not known yet whether the video service sit in the existing Instagram app or have be built on a separate app platform.
With invites to the event headlined with “A small team has been working on a big idea” it’s suggested that Instagram’s move into offering a video service has been triggered by the success of Vine. Vine’s standalone video-sharing app for Twitter has been downloaded some 13 million times on the iPhone since the start of the year. It’s Android app, only made available since the start of this month has already enjoyed around 5 million downloads.
As the most established photo-sharing service Instagram has over 100 million users – and Facebook serves around 15 billion images every day. So Instagram clearly has an established user base, which provided any new service is launched sympathetically to user’s feedback (rather than the PR disaster that was Instagram’s rollout of new terms and conditions which saw users flee the service) could prove an instant hit and block any further rapid expansion of Vine. Instagram’s hugely popular visual effects could be put to use on the video service. Those who have much to lose from such a move may not only be Vine, but apps such as SocialCam and Viddy.
But are the rumours simply wrong? Some have suggested that the second line of Facebook’s invite hints at something much bigger than just an extension to Instagram’s existing service.
“Join us for coffee and learn about a new product.”
TechCrunch has suggested that this could be a news reader service, timed to launch just as Google Reader shuts down. Perhaps Facebook will prove us all wrong and launch something else and take us, tech-geeks and investors all by surprise.
James Barnes, StatusCake.com
Share this
5 min read AI Has Made Building Monitoring Easy. It Hasn’t Made Owning It Any Easier. A few months ago, I spoke to an engineering manager who proudly told me they had rebuilt their monitoring stack over a long weekend. They’d used AI to scaffold synthetic checks. They’d generated alert logic with dynamic thresholds. They’d then wired everything
3 min read In the previous posts, we’ve looked at how alert noise emerges from design decisions, why notification lists fail to create accountability, and why alerts only work when they’re designed around a clear outcome. Taken together, these ideas point to a broader conclusion. That alerting is not just a technical system, it’s a socio-technical one. Alerting
3 min read In the first two posts of this series, we explored how alert noise emerges from design decisions, and why notification lists fail to create accountability when responsibility is unclear. There’s a deeper issue underneath both of those problems. Many alerting systems are designed without being clear about the outcome they’re meant to produce. When teams
3 min read In the previous post, we looked at how alert noise is rarely accidental. It’s usually the result of sensible decisions layered over time, until responsibility becomes diffuse and response slows. One of the most persistent assumptions behind this pattern is simple. If enough people are notified, someone will take responsibility. After more than fourteen years
3 min read In a previous post, The Incident Checklist: Reducing Cognitive Load When It Matters Most, we explored how incidents stop being purely technical problems and become human ones. These are moments where decision-making under pressure and cognitive load matter more than perfect root cause analysis. When systems don’t support people clearly in those moments, teams compensate.
4 min read In the previous post, we looked at what happens after detection; when incidents stop being purely technical problems and become human ones, with cognitive load as the real constraint. This post assumes that context. The question here is simpler and more practical. What actually helps teams think clearly and act well once things are already
Find out everything you need to know in our new uptime monitoring whitepaper 2021