Points of presence

The Fastly network comprises a large number of physical servers distributed all over the world, connected to the internet at high density internet exchange points.

Sites and points of presence

Fastly servers are grouped into:

  • "sites", which describes a co-located set of machines in a single physical facility, attached to the same internet transit; and
  • "points of presence" (commonly "POPs"), which describes the clustering of multiple machines together to create a single pool of cache storage.

In many cases, all the machines that comprise one site also comprise one POP (i.e., POP == site), with the POP and the site sharing the same name. The largest POPs in densely populated metropolitan areas may span multiple sites, with locations and connectivity chosen to serve the same human population. See metro POPs.

In VCL services, the server.datacenter variable reports the identity of the POP, while server.hostname includes the ID of the site. The server.identity variable includes the ID of both the site and the POP.

Due to the effects of clustering, a single request to a Fastly service may be processed by servers in more than one site, even while remaining within the same POP. However, transit between servers in different sites within the same POP is extremely fast, and comparable to the latency between servers on the same site.

If a service has shielding enabled, a request that is not satisfiable from cache will transit two POPs. With clustering also enabled (which is the case by default), the request may encounter a maximum of two POPs and four sites on its way to origin, as illustrated below:

Illustration of a shielded request going through a multi-site POP

Both POPs and sites use three-letter codes as identifiers, derived from the IATA airport code of a nearby airport. However, since POPs are rotated into and out of service regularly, codes are allocated based on availability and the location of the airport is not necessarily an accurate guide to the location of the Fastly site.

NOTE: Although we have historically used the term data center to refer to both a POP and a site, current use of the term "data center" may refer to POPs or sites depending on the context. Be sure you understand which concept is being referred to. The server.datacenter variable, for example, refers to a POP.

A list of all POPs currently in service is shown below, and is also available via the API and the Fastly CLI. Our network map also shows locations of all current Fastly POPs as well as planned future POPs and POP expansions. Announcements of POPs entering and leaving service, or of substantial changes to POP capacity, are made on our service status page.

Metro POPs

In the case of most Fastly POPs, the POP occupies a single site, which has the same name as the POP. Where a POP spreads across multiple physical sites it is known as a metro POP. The following are metro POPs currently in service:

LocationPOP IdentifierSites spanned
AshburnIADKCGS720, KIAD700, KJYO710
AtlantaPDKKATL184, KFTY213, KPDK178
ChicagoCHIKIGQ800, KLOT810
DallasDFWKDAL212, KDFW821
FrankfurtFRAEDDF823, ETOU822
Sao PauloGRUSBGR193, SBSP209
SeattleBFIKBFI740, KRNT730

Metro POPs have the largest cache capacity on the Fastly network and are therefore good choices for shield locations.

POP-specific edge behavior

If you need to know which POP is currently processing a request in edge logic, you can do so in both VCL and Compute services.

  • In VCL, see the server.datacenter variable
  • In a Compute program, use the FASTLY_POP environment variable

Be aware that POPs are added and removed from the Fastly network regularly, and any logic created to vary the behavior of your service based on POP locations may need frequent maintenance.

Effects of POP and site variability

The design of the Fastly network balances issues such as provider diversity, connectivity, traffic volume, and optimum cache size. For Fastly customers, POP variability is most notable in its effect on cache hit ratio (i.e., the ratio of inbound requests that are able to be satisfied from cache).

For example, 100 requests handled by 100 distinct servers in 100 distinct POPs will experience a much lower cache hit ratio than 100 requests handled by 100 distinct servers all participating in the same POP because, in the latter case, all the requests have access to the same shared pool of cache storage.

Other features provided by Fastly are unaffected by POP variability, such as our image optimizer, which is available on all Fastly servers.

The effects of site variability are negligible and likely undetectable.

Complete list of POPs

The following table lists all POPs current active in the Fastly network:

LocationPOP IdentifierApprox location
AdelaideADL-34.9285, 138.6007
AmsterdamAMS52.308613, 4.763889
AshburnDCA38.944533, -77.455811
AshburnIAD38.944533, -77.455811
AtlantaPDK33.876819, -84.302921
AucklandAKL-37.008056, 174.791667
BangkokBKK13.756, 100.501
BogotaBOG4.711, -74.072
BostonBOS42.364347, -71.005181
BrisbaneBNE-27.384167, 153.1175
BrusselsBRU50.871, 4.476
Buenos AiresEZE-34.815, -58.5348
CalgaryYYC51.047, -114.08
Cape TownCPT-33.97, 18.464
ChennaiMAA12.9941, 80.1709
ChicagoCHI41.863, -87.641
ChristchurchCHC-43.532, 172.636
ColumbusCMH40.116, -83.002
ColumbusLCK40.116, -83.002
CopenhagenCPH55.728081, 12.37752
CuritibaCWB-25.4809, -49.3044
DallasADS32.896828, -97.037997
DallasDFW32.896828, -97.037997
DelhiDEL28.506912, 77.378557
DenverDEN39.861656, -104.673178
DetroitDTW42.448, -83.263
DubaiDXB25.032, 55.19
DublinDUB53.35, -6.26
FortalezaFOR-3.735, -38.458
FrankfurtFRA50.026421, 8.543125
FrankfurtWIE50.11975, 8.738472
Fujairah Al MahtaFJR25.112225, 56.323964
GainesvilleGNV29.6516, -82.3248
GhanaACC5.573, -0.203
HelsinkiHEL60.1699, 24.9384
Hong KongHKG22.308919, 113.914603
HonoluluHNL21.364, -157.869
HoustonIAH29.99022, -95.336783
HyderabadHYD17.442, 78.378
JohannesburgJNB-26.13778, 28.19756
Kansas CityMCI39.101, -94.581
KolkataCCU22.588, 88.393
Kuala LumpurKUL3.149, 101.706
LimaLIM-12.088902, -76.973405
LisbonLIS38.788, -9.123
LondonLCY51.505278, 0.055278
LondonLHR51.4775, -0.461389
LondonLON51.499, -0.011
Los AngelesBUR34.198312, -118.357404
Los AngelesLAX33.942536, -118.408075
MadridMAD40.439323, -3.621211
ManchesterMAN53.4808, -2.2426
ManilaMNL14.566, 121.022
MarseilleMRS43.311, 5.373
MelbourneMEL-37.673333, 144.843333
MiamiMIA25.79325, -80.290556
MilanLIN45.47, 9.036
MilanMXP45.4642, 9.19
MinneapolisMSP44.971401, -93.254501
MinneapolisSTP44.971401, -93.254501
MontrealYUL45.497497, -73.570959
MumbaiBOM18.975, 72.825833
MunichMUC48.143, 11.555
New York CityLGA40.639751, -73.778925
New York CityNYC40.778, -74.073
NewarkEWR40.736844, -74.173402
OsakaITM34.785528, 135.438222
OsloOSL59.922, 10.809
PalermoPMO38.1607109, 13.3157489
Palo AltoPAO37.454965, -122.110783
ParisPAR48.856654, 2.38532
PerthPER-31.940278, 115.966944
PhoenixPHX33.396, -111.97
PortlandPDX45.552, -122.914
Rio de JaneiroGIG-22.81341, -43.249423
RomeFCO41.89891, 12.51206
San JoseSJC37.3626, -121.929022
San JoseWVI37.242, -121.782
SantiagoSCL-33.3936, -70.7935
Sao PauloGRU-23.432075, -46.469511
SeattleBFI47.449, -122.309306
SeoulICN36.38, 128.124
SingaporeQPG1.350189, 103.994433
SofiaSOF42.703, 23.306
St.LouisSTL38.629, -90.197
StockholmBMA59.354372, 17.94165
SydneySYD-33.946111, 151.177222
TokyoHND35.622281, 139.748426
TokyoNRT35.617, 139.748
TokyoTYO35.617, 139.748
TorontoYYZ43.677223, -79.630556
VancouverYVR49.1967, -123.1815
ViennaVIE48.269, 16.41
WellingtonWLG-41.327221, 174.805278