Considerations for Large Authoritative DNS Servers Operators

Document Type Active Internet-Draft (individual)
Authors Giovane Moura  , Wes Hardaker  , John Heidemann  , Marco Davids 
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DNSOP Working Group                                         G.C.M. Moura
Internet-Draft                                        SIDN Labs/TU Delft
Intended status: Informational                               W. Hardaker
Expires: 8 July 2022                                        J. Heidemann
                                      USC/Information Sciences Institute
                                                               M. Davids
                                                               SIDN Labs
                                                          4 January 2022

      Considerations for Large Authoritative DNS Servers Operators


   Recent research work has explored the deployment characteristics and
   configuration of the Domain Name System (DNS).  This document
   summarizes the conclusions from these research efforts and offers
   specific, tangible considerations or advice to authoritative DNS
   server operators.  Authoritative server operators may wish to follow
   these considerations to improve their DNS services.

   It is possible that the results presented in this document could be
   applicable in a wider context than just the DNS protocol, as some of
   the results may generically apply to any stateless/short-duration,
   anycasted service.

   This document is not an IETF consensus document: it is published for
   informational purposes.

Status of This Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
   Task Force (IETF).  Note that other groups may also distribute
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   Drafts is at

   Internet-Drafts are draft documents valid for a maximum of six months
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   material or to cite them other than as "work in progress."

   This Internet-Draft will expire on 8 July 2022.

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Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
   2.  Background  . . . . . . . . . . . . . . . . . . . . . . . . .   3
   3.  Considerations  . . . . . . . . . . . . . . . . . . . . . . .   5
     3.1.  C1: Deploy anycast in every authoritative server to enhance
           distribution and latency  . . . . . . . . . . . . . . . .   5
       3.1.1.  Research background . . . . . . . . . . . . . . . . .   5
       3.1.2.  Resulting considerations  . . . . . . . . . . . . . .   6
     3.2.  C2: Optimizing routing is more important than location
           count and diversity . . . . . . . . . . . . . . . . . . .   7
       3.2.1.  Research background . . . . . . . . . . . . . . . . .   7
       3.2.2.  Resulting considerations  . . . . . . . . . . . . . .   8
     3.3.  C3: Collecting anycast catchment maps to improve
           design  . . . . . . . . . . . . . . . . . . . . . . . . .   8
       3.3.1.  Research background . . . . . . . . . . . . . . . . .   8
       3.3.2.  Resulting considerations  . . . . . . . . . . . . . .   9
     3.4.  C4: When under stress, employ two strategies  . . . . . .   9
       3.4.1.  Research background . . . . . . . . . . . . . . . . .  10
       3.4.2.  Resulting considerations  . . . . . . . . . . . . . .  11
     3.5.  C5: Consider longer time-to-live values whenever
           possible  . . . . . . . . . . . . . . . . . . . . . . . .  11
       3.5.1.  Research background . . . . . . . . . . . . . . . . .  11
       3.5.2.  Resulting considerations  . . . . . . . . . . . . . .  13
     3.6.  C6: Consider the TTL differences between parents and
           children  . . . . . . . . . . . . . . . . . . . . . . . .  14
       3.6.1.  Research background . . . . . . . . . . . . . . . . .  14
       3.6.2.  Resulting considerations  . . . . . . . . . . . . . .  15
   4.  Security considerations . . . . . . . . . . . . . . . . . . .  15
   5.  Privacy Considerations  . . . . . . . . . . . . . . . . . . .  15
   6.  IANA considerations . . . . . . . . . . . . . . . . . . . . .  15
   7.  Acknowledgements  . . . . . . . . . . . . . . . . . . . . . .  15
   8.  References  . . . . . . . . . . . . . . . . . . . . . . . . .  16
     8.1.  Normative References  . . . . . . . . . . . . . . . . . .  16

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     8.2.  Informative References  . . . . . . . . . . . . . . . . .  17
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  20

1.  Introduction

   This document summarizes recent research work that explored the
   deployed DNS configurations and offers derived, specific tangible
   advice to DNS authoritative server operators (DNS operators
   hereafter).  The considerations (C1--C5) presented in this document
   are backed by peer-reviewed research works, which used wide-scale
   Internet measurements to draw their conclusions.  This document
   summarizes the research results and describes the resulting key
   engineering options.  In each section, it points readers to the
   pertinent publications where additional details are presented.

   These considerations are designed for operators of "large"
   authoritative DNS servers.  In this context, "large" authoritative
   servers refers to those with a significant global user population,
   like top-level domain (TLD) operators, run by either a single or
   multiple operators.  Typically these networks are deployed on wide
   anycast networks [RFC1546][AnyBest].  These considerations may not be
   appropriate for smaller domains, such as those used by an
   organization with users in one unicast network, or in one city or
   region, where operational goals such as uniform, global low latency
   are less required.

   It is possible that the results presented in this document could be
   applicable in a wider context than just the DNS protocol, as some of
   the results may generically apply to any stateless/short-duration,
   anycasted service.  Because the conclusions of the reviewed studies
   don't measure smaller networks, the wording in this document
   concentrates solely on disusing large-scale DNS authoritative
   services only.

   This document is not an IETF consensus document: it is published for
   informational purposes.

2.  Background

   The DNS has main two types of DNS servers: authoritative servers and
   recursive resolvers, shown by a representational deployment model in
   Figure 1.  An authoritative server (shown as AT1--AT4 in Figure 1)
   knows the content of a DNS zone, and is responsible for answering
   queries about that zone.  It runs using local (possibly automatically
   updated) copies of the zone and does not need to query other servers
   [RFC2181] in order to answer requests.  A recursive resolver (Re1--
   Re3) is a server that iteratively queries authoritative and other
   servers to answer queries received from client requests [RFC1034].  A

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   client typically employs a software library called a stub resolver
   (stub in Figure 1) to issue its query to the upstream recursive
   resolvers [RFC1034].

           +-----+  +-----+  +-----+  +-----+
           | AT1 |  | AT2 |  | AT3 |  | AT4 |
           +-----+  +-----+  +-----+  +-----+
             ^         ^        ^        ^
             |         |        |        |
             |      +-----+     |        |
             +------| Re1 |----+|        |
             |      +-----+              |
             |         ^                 |
             |         |                 |
             |      +----+   +----+      |
             +------|Re2 |   |Re3 |------+
                    +----+   +----+
                      ^          ^
                      |          |
                      | +------+ |
                      +-| stub |-+

        Figure 1: Relationship between recursive resolvers (Re) and
                      authoritative name servers (ATn)

   DNS queries issued by a client contribute to a user's perceived
   perceived latency and affect user experience [Singla2014] depending
   on how long it takes for responses to be returned.  The DNS system
   has been subject to repeated Denial of Service (DoS) attacks (for
   example, in November 2015 [Moura16b]) in order to specifically
   degrade user experience.

   To reduce latency and improve resiliency against DoS attacks, the DNS
   uses several types of service replication.  Replication at the
   authoritative server level can be achieved with (i) the deployment of
   multiple servers for the same zone [RFC1035] (AT1---AT4 in Figure 1),
   (ii) the use of IP anycast [RFC1546][RFC4786][RFC7094] that allows
   the same IP address to be announced from multiple locations (each of
   referred to as an "anycast instance" [RFC8499]) and (iii) the use of
   load balancers to support multiple servers inside a single
   (potentially anycasted) instance.  As a consequence, there are many
   possible ways an authoritative DNS provider can engineer its
   production authoritative server network, with multiple viable choices
   and no necessarily single optimal design.

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3.  Considerations

   In the next sections we cover the specific consideration (C1--C6) for
   conclusions drawn within the academic papers about large
   authoritative DNS server operators.  These considerations are
   conclusions reached from academic works that authoritative server
   operators may wish to consider in order to improve their DNS service.
   Each consideration offers different improvements that may impact
   service latency, routing, anycast deployment, and defensive
   strategies for example.

3.1.  C1: Deploy anycast in every authoritative server to enhance
      distribution and latency

3.1.1.  Research background

   Authoritative DNS server operators announce their service using NS
   records[RFC1034].  Different authoritative servers for a given zone
   should return the same content; typically they stay synchronized
   using DNS zone transfers (AXFR[RFC5936] and IXFR[RFC1995]),
   coordinating the zone data they all return to their clients.

   As discussed above, the DNS heavily relies upon replication to
   support high reliability, ensure capacity and to reduce latency
   [Moura16b].  DNS has two complementary mechanisms for service
   replication: nameserver replication (multiple NS records) and anycast
   (multiple physical locations).  Nameserver replication is strongly
   recommended for all zones (multiple NS records), and IP anycast is
   used by many larger zones such as the DNS Root[AnyFRoot], most top-
   level domains[Moura16b] and many large commercial enterprises,
   governments and other organizations.

   Most DNS operators strive to reduce service latency for users, which
   is greatly affected by both of these replication techniques.
   However, because operators only have control over their authoritative
   servers, and not over the client's recursive resolvers, it is
   difficult to ensure that recursives will be served by the closest
   authoritative server.  Server selection is ultimately up to the
   recursive resolver's software implementation, and different vendors
   and even different releases employ different criteria to chose the
   authoritative servers with which to communicate.

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   Understanding how recursive resolvers choose authoritative servers is
   a key step in improving the effectiveness of authoritative server
   deployments.  To measure and evaluate server deployments,
   [Mueller17b] deployed seven unicast authoritative name servers in
   different global locations and then queried them from more than 9000
   RIPE authoritative server operators and their respective recursive

   [Mueller17b] found that recursive resolvers in the wild query all
   available authoritative servers, regardless of the observed latency.
   But the distribution of queries tends to be skewed towards
   authoritatives with lower latency: the lower the latency between a
   recursive resolver and an authoritative server, the more often the
   recursive will send queries to that server.  These results were
   obtained by aggregating results from all of the vantage points and
   were not specific to any specific vendor or version.

   The authors believe this behavior is a consequence of combining the
   two main criteria employed by resolvers when selecting authoritative
   servers: resolvers regularly check all listed authoritative servers
   in an NS set to determine which is closer (the least latent) and when
   one isn't available selects one of the alternatives.

3.1.2.  Resulting considerations

   For an authoritative DNS operator, this result means that the latency
   of all authoritative servers (NS records) matter, so they all must be
   similarly capable -- all available authoritatives will be queried by
   most recursive resolvers.  Unicasted services, unfortunately, cannot
   deliver good latency worldwide (a unicast authoritative server in
   Europe will always have high latency to resolvers in California and
   Australia, for example, given its geographical distance).

   [Mueller17b] recommends that DNS operators deploy equally strong IP
   anycast instances for every authoritative server (i.e., for each NS
   record).  Each large authoritative DNS server provider should phase
   out their usage of unicast and deploy a well engineered number of
   anycast instances with good peering strategies so they can provide
   good latency to their global clients.

   As a case study, the ".nl" TLD zone was originally served on seven
   authoritative servers with a mixed unicast/anycast setup.  In early
   2018, .nl moved to a setup with 4 anycast authoritative servers.

   [Mueller17b]'s contribution to DNS service engineering shows that
   because unicast cannot deliver good latency worldwide, anycast needs
   to be used to provide a low latency service worldwide.

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3.2.  C2: Optimizing routing is more important than location count and

3.2.1.  Research background

   When selecting an anycast DNS provider or setting up an anycast
   service, choosing the best number of anycast
   instances[RFC4786][RFC7094] to deploy is a challenging problem.
   Selecting where and how many global locations to announce from using
   BGP is tricky.  Intuitively, one could naively think that the more
   instances the better and simply "more" will always lead to shorter
   response times.

   This is not necessarily true, however.  In fact, [Schmidt17a] found
   that proper route engineering can matter more than the total number
   of locations.  They analyzed the relationship between the number of
   anycast instances and service performance (measuring latency of the
   round-trip time (RTT)), measuring the overall performance of four DNS
   Root servers.  The Root DNS servers are implemented by 12 separate
   organizations serving the DNS root zone at 13 different IPv4/IPv6
   address pairs.

   The results documented in [Schmidt17a] measured the performance of
   the {c,f,k,l} (hereafter, "C", "F", "K" and "L")
   servers from more than 7.9k RIPE Atlas probes.  RIPE Atlas is a
   Internet measurement platform with more than 12000 global vantage
   points called "Atlas Probes" -- it is used regularly by both
   researchers and operators [RipeAtlas15a] [RipeAtlas19a].

   [Schmidt17a] found that the C server, a smaller anycast deployment
   consisting of only 8 instances, provided very similar overall
   performance in comparison to the much larger deployments of K and L,
   with 33 and 144 instances respectively.  The median RTT for C, K and
   L root server were all between 30-32ms.

   Because RIPE Atlas is known to have better coverage in Europe than
   other regions, the authors specifically analyzed the results per
   region and per country (Figure 5 in [Schmidt17a]), and show that
   known Atlas bias toward Europe does not change the conclusion that
   properly selected anycast locations is more important to latency than
   the number of sites.

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3.2.2.  Resulting considerations

   The important conclusion of [Schmidt17a] is that when engineering
   anycast services for performance, factors other than just the number
   of instances (such as local routing connectivity) must be considered.
   Specifically, optimizing routing policies is more important than
   simply adding new instances.  They showed that 12 instances can
   provide reasonable latency, assuming they are globally distributed
   and have good local interconnectivity.  However, additional instances
   can still be useful for other reasons, such as when handling Denial-
   of-service (DoS) attacks [Moura16b].

3.3.  C3: Collecting anycast catchment maps to improve design

3.3.1.  Research background

   An anycast DNS service may be deployed from anywhere from several
   locations to hundreds of locations (for example,
   has over 150 anycast instances at the time this was written).
   Anycast leverages Internet routing to distribute incoming queries to
   a service's hop-nearest distributed anycast locations.  However,
   usually queries are not evenly distributed across all anycast
   locations, as found in the case of L-Root [IcannHedge18].

   Adding locations to or removing locations from a deployed anycast
   network changes the load distribution across all of its locations.
   When a new location is announced by BGP, locations may receive more
   or less traffic than it was engineered for, leading to suboptimal
   service performance or even stressing some locations while leaving
   others underutilized.  Operators constantly face this scenario that
   when expanding an anycast service.  Operators cannot easily directly
   estimate future query distributions based on proposed anycast network
   engineering decisions.

   To address this need and estimate the query loads based on changing,
   in particular expanding, anycast service changes [Vries17b] developed
   a new technique enabling operators to carry out active measurements,
   using an open-source tool called Verfploeter (available at
   [VerfSrc]).  The results allow the creation of detailed anycast maps
   and catchment estimates.  By running verfploeter combined with a
   published IPv4 "hit list", DNS can precisely calculate which remote
   prefixes will be matched to each anycast instance in a network.  At
   the moment of this writing, Verfploeter still does not support IPv6
   as the IPv4 hit lists used are generated via frequent large scale
   ICMP echo scans, which is not possible using IPv6.

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   As proof of concept, [Vries17b] documents how it verfploeter was used
   to predict both the catchment and query load distribution for a new
   anycast instance deployed for  Using two anycast
   test instances in Miami (MIA) and Los Angeles (LAX), an ICMP echo
   query was sent from an IP anycast addresses to each IPv4 /24 network
   routing block on the Internet.

   The ICMP echo responses were recorded at both sites and analyzed and
   overlayed onto a graphical world map, resulting in an Internet scale
   catchment map.  To calculate expected load once the production
   network was enabled, the quantity of traffic received by b.root-'s single site at LAX was recorded based on a single day's
   traffic (2017-04-12, DITL datasets [Ditl17]).  [Vries17b] predicted
   that 81.6% of the traffic load would remain at the LAX site.  This
   estimate by verfploeter turned out to be very accurate; the actual
   measured traffic volume when production service at MIA was enabled
   was 81.4%.

   Verfploeter can also be used to estimate traffic shifts based on
   other BGP route engineering techniques (for example, AS path
   prepending or BGP community use) in advance of operational
   deployment.  [Vries17b] studied this using prepending with 1-3 hops
   at each instance and compared the results against real operational
   changes to validate the techniques accuracy.

3.3.2.  Resulting considerations

   An important operational takeaway [Vries17b] provides is how DNS
   operators can make informed engineering choices when changing DNS
   anycast network deployments by using Verfploeter in advance.
   Operators can identify sub-optimal routing situations in advance with
   significantly better coverage than using other active measurement
   platforms such as RIPE Atlas.  To date, Verfploeter has been deployed
   on a operational testbed (Anycast testbed) [AnyTest], on a large
   unnamed operator and is run daily at[Vries17b].

   Operators should use active measurement techniques like Verfploeter
   in advance of potential anycast network changes to accurately measure
   the benefits and potential issues ahead of time.

3.4.  C4: When under stress, employ two strategies

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3.4.1.  Research background

   DDoS attacks are becoming bigger, cheaper, and more frequent
   [Moura16b].  The most powerful recorded DDoS attack against DNS
   servers to date reached 1.2 Tbps by using IoT devices [Perlroth16].
   How should a DNS operator engineer its anycast authoritative DNS
   server react to such a DDoS attack?  [Moura16b] investigates this
   question using empirical observations grounded with theoretical
   option evaluations.

   An authoritative DNS server deployed using anycast will have many
   server instances distributed over many networks.  Ultimately, the
   relationship between the DNS provider's network and a client's ISP
   will determine which anycast instance will answer queries for a given
   client, given that BGP is the protocol that maps clients to specific
   anycast instances by using routing information [RF:KDar02].  As a
   consequence, when an anycast authoritative server is under attack,
   the load that each anycast instance receives is likely to be unevenly
   distributed (a function of the source of the attacks), thus some
   instances may be more overloaded than others which is what was
   observed analyzing the Root DNS events of Nov. 2015 [Moura16b].
   Given the fact that different instances may have different capacity
   (bandwidth, CPU, etc.), making a decision about how to react to
   stress becomes even more difficult.

   In practice, an anycast instance is overloaded with incoming traffic,
   operators have two options:

   *  They can withdraw its routes, pre-prepend its AS route to some or
      all of its neighbors, perform other traffic shifting tricks (such
      as reducing route announcement propagation using BGP
      communities[RFC1997]), or by communicating with its upstream
      network providers to apply filtering (potentially using FlowSpec
      [RFC8955] or DOTS protocol ([RFC8811], [RFC8782], [RFC8783]).
      These techniques shift both legitimate and attack traffic to other
      anycast instances (with hopefully greater capacity) or to block
      traffic entirely.

   *  Alternatively, operators can be become a degraded absorber by
      continuing to operate, knowing dropping incoming legitimate
      requests due to queue overflow.  However, this approach will also
      absorb attack traffic directed toward its catchment, hopefully
      protecting the other anycast instances.

   [Moura16b] saw both of these behaviors deployed in practice by
   studying instance reachability and route-trip time (RTTs) in the DNS
   root events.  When withdraw strategies were deployed, the stress of
   increased query loads were displaced from one instance to multiple

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   other sites.  In other observed events, one site was left to absorb
   the brunt of an attack leaving the other sites to remain relatively
   less affected.

3.4.2.  Resulting considerations

   Operators should consider having both a anycast site withdraw
   strategy and a absorption strategy ready to be used before a network
   overload occurs.  Operators should be able to deploy one or both of
   these strategies rapidly.  Ideally, these should be encoded into
   operating playbooks with defined site measurement guidelines for
   which strategy to employ based on measured data from past events.

   [Moura16b] speculates that careful, explicit, and automated
   management policies may provide stronger defenses to overload events.
   DNS operators should be ready to employ both traditional filtering
   approaches and other routing load balancing techniques
   (withdraw/prepend/communities or isolate instances), where the best
   choice depends on the specifics of the attack.

   Note that this consideration refers to the operation of just one
   anycast service point, i.e., just one anycasted IP address block
   covering one NS record.  However, DNS zones with multiple
   authoritative anycast servers may also expect loads to shift from one
   anycasted server to another, as resolvers switch from on
   authoritative service point to another when attempting to resolve a
   name [Mueller17b].

3.5.  C5: Consider longer time-to-live values whenever possible

3.5.1.  Research background

   Caching is the cornerstone of good DNS performance and reliability.
   A 50 ms response to a new DNS query may be considered fast, but a
   less than 1 ms response to a cached entry is far faster.  [Moura18b]
   showed that caching also protects users from short outages and even
   significant DDoS attacks.

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   DNS record TTLs (time-to-live values) [RFC1034][RFC1035] directly
   control cache durations and affect latency, resilience, and the role
   of DNS in CDN server selection.  Some early work modeled caches as a
   function of their TTLs [Jung03a], and recent work has examined their
   interaction with DNS[Moura18b], but until [Moura19b] no research
   provided considerations about the benefits of various TTL value
   choices.  To study this, Moura et. al.  [Moura19b] carried out a
   measurement study investigating TTL choices and their impact on user
   experiences in the wild.  They performed this study independent of
   specific resolvers (and their caching architectures), vendors, or

   First, they identified several reasons why operators and zone-owners
   may want to choose longer or shorter TTLs:

   *  As discussed, longer TTLs lead to a longer cache life, resulting
      in faster responses.  [Moura19b] measured this in the wild and
      showed that by increasing the TTL for .uy TLD from 5 minutes
      (300s) to 1 day (86400s) the latency measured from 15k Atlas
      vantage points changed significantly: the median RTT decreased
      from 28.7ms to 8ms, and the 75%ile decreased from 183ms to 21ms.

   *  Longer caching times also results in lower DNS traffic:
      authoritative servers will experience less traffic with extended
      TTLs, as repeated queries are answered by resolver caches.

   *  Consequently, longer caching results in a lower overall cost if
      DNS is metered: some DNS-As-A-Service providers charge a per query
      (metered) cost (often in addition to a fixed monthly cost).

   *  Longer caching is more robust to DDoS attacks on DNS
      infrastructure.  [Moura18b] also measured and show that DNS
      caching can greatly reduce the effects of a DDoS on DNS, provided
      that caches last longer than the attack.

   *  However, shorter caching supports deployments that may require
      rapid operational changes: An easy way to transition from an old
      server to a new one is to simply change the DNS records.  Since
      there is no method to remotely remove cached DNS records, the TTL
      duration represents a necessary transition delay to fully shift
      from one server to another.  Thus, low TTLs allow for more rapid
      transitions.  However, when deployments are planned in advance
      (that is, longer than the TTL), it is possible to lower the TTLs
      just-before a major operational change and raise them again

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   *  Shorter caching can also help with a DNS-based response to DDoS
      attacks.  Specifically, some DDoS-scrubbing services use the DNS
      to redirect traffic during an attack.  Since DDoS attacks arrive
      unannounced, DNS-based traffic redirection requires the TTL be
      kept quite low at all times to allow operators to suddenly have
      their zone served by a DDoS-scrubbing service.

   *  Shorter caching helps DNS-based load balancing.  Many large
      services are known to rotate traffic among their servers using
      DNS-based load balancing.  Each arriving DNS request provides an
      opportunity to adjust service load by rotating IP address records
      (A and AAAA) to the lowest unused server.  Shorter TTLs may be
      desired in these architectures to react more quickly to traffic
      dynamics.  Many recursive resolvers, however, have minimum caching
      times of tens of seconds, placing a limit on this form of agility.

3.5.2.  Resulting considerations

   Given these considerations, the proper choice for a TTL depends in
   part on multiple external factors -- no single recommendation is
   appropriate for all scenarios.  Organizations must weigh these trade-
   offs and find a good balance for their situation.  Still, some
   guidelines can be reached when choosing TTLs:

   *  For general DNS zone owners, [Moura19b] recommends a longer TTL of
      at least one hour, and ideally 8, 12, or 24 hours.  Assuming
      planned maintenance can be scheduled at least a day in advance,
      long TTLs have little cost and may, even, literally provide a cost

   *  For registry operators: TLD and other public registration
      operators (for example most ccTLDs and .com, .net, .org) that host
      many delegations (NS records, DS records and "glue" records),
      [Moura19b] demonstrates that most resolvers will use the TTL
      values provided by the child delegations while the others some
      will choose the TTL provided by the parent's copy of the record.
      As such, [Moura19b] recommends longer TTLs (at least an hour or
      more) for registry operators as well for child NS and other

   *  Users of DNS-based load balancing or DDoS-prevention services may
      require shorter TTLs: TTLs may even need to be as short as 5
      minutes, although 15 minutes may provide sufficient agility for
      many operators.  There is always a tussle between shorter TTLs
      providing more agility against all the benefits listed above for
      using longer TTLs.

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   *  Use of A/AAAA and NS records: The TTLs for A/AAAA records should
      be shorter to or equal to the TTL for the corresponding NS records
      for in-bailiwick authoritative DNS servers, since [Moura19b] finds
      that once an NS record expires, their associated A/AAAA will also
      be re-queried when glue is required to be sent by the parents.
      For out-of-bailiwick servers, A, AAAA and NS records are usually
      all cached independently, so different TTLs can be used
      effectively if desired.  In either case, short A and AAAA records
      may still be desired if DDoS-mitigation services are required.

3.6.  C6: Consider the TTL differences between parents and children

3.6.1.  Research background

   Multiple record types exist or are related between the parent of a
   zone and the child.  At a minimum, NS records are supposed to be
   identical in the parent (but often are not) as or corresponding IP
   address in "glue" A/AAAA records that must exist for in-bailiwick
   authoritative servers.  Additionally, if DNSSEC ([RFC4033] [RFC4034]
   [RFC4035] [RFC4509]) is deployed for a zone the parent's DS record
   must cryptographically refer to a child's DNSKEY record.

   Because some information exists in both the parent and a child, it is
   possible for the TTL values to differ between the parent's copy and
   the child's.  [Moura19b] examines resolver behaviors when these
   values differ in the wild, as they frequently do -- often parent
   zones have defacto TTL values that a child has no control over.  For
   example, NS records for TLDs in the root zone are all set to 2 days
   (48 hours), but some TLD's have lower values within their published
   records (the TTLs for .cl's NS records from their authoritative
   servers is 1 hour).  [Moura19b] also examines the differences in the
   TTLs between the NS records and the corresponding A/AAAA records for
   the addresses of a nameserver.  RIPE Atlas nodes are used to
   determine what resolvers in the wild do with different information,
   and whether the parent's TTL is used for cache life-times ("parent-
   centric") or the child's is used ("child-centric").

   [Moura19b] finds that roughly 90% of resolvers follow the child's
   view of the TTL, while 10% appear parent-centric.  It additionally
   finds that resolvers behave differently for cache lifetimes for in-
   bailiwick vs out-of-bailiwick NS/A/AAAA TTL combinations.
   Specifically, when NS TTLs are shorter than the corresponding address
   records, most resolvers will re-query for A/AAAA records for in-
   bailiwick resolvers and switch to new address records even if the
   cache indicates the original A/AAAA records could be kept longer.  On
   the other hand, the inverse is true for out-of-bailiwick resolvers:
   If the NS record expires first resolvers will honor the original
   cache time of the nameserver's address.

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3.6.2.  Resulting considerations

   The important conclusion from this study is that operators cannot
   depend on their published TTL values alone -- the parent's values are
   also used for timing cache entries in the wild.  Operators that are
   planning on infrastructure changes should assume that older
   infrastructure must be left on and operational for at least the
   maximum of both the parent and child's TTLs.

4.  Security considerations

   This document discusses applying measured research results to
   operational deployments.  Most of the considerations affect mostly
   operational practice, though a few do have security related impacts.

   Specifically, C4 discusses a couple of strategies to employ when a
   service is under stress from DDoS attacks and offers operators
   additional guidance when handling excess traffic.

   Similarly, C5 identifies the trade-offs with respect to the
   operational and security benefits of using longer time-to-live

5.  Privacy Considerations

   This document does not add any practical new privacy issues, aside
   from possible benefits in deploying longer TTLs as suggested in C5.
   Longer TTLs may help preserve a user's privacy by reducing the number
   of requests that get transmitted in both the client-to-resolver and
   resolver-to-authoritative cases.

6.  IANA considerations

   This document has no IANA actions.

7.  Acknowledgements

   This document is a summary of the main considerations of six research
   works performed by the authors and others.  This document would not
   have been possible without the hard work of these authors and co-

   *  Ricardo de O.  Schmidt

   *  Wouter B de Vries

   *  Moritz Mueller

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   *  Lan Wei

   *  Cristian Hesselman

   *  Jan Harm Kuipers

   *  Pieter-Tjerk de Boer

   *  Aiko Pras

   We would like also to thank the reviewers of this draft that offered
   valuable suggestions: Duane Wessels, Joe Abley, Toema Gavrichenkov,
   John Levine, Michael StJohns, Kristof Tuyteleers, Stefan Ubbink,
   Klaus Darilion and Samir Jafferali, and comments provided at the IETF
   DNSOP session (IETF104).

   Besides those, we would like thank those acknowledged in the papers
   this document summarizes for helping produce the results: RIPE NCC
   and DNS OARC for their tools and datasets used in this research, as
   well as the funding agencies sponsoring the individual research

8.  References

8.1.  Normative References

   [RFC1034]  Mockapetris, P., "Domain names - concepts and facilities",
              STD 13, RFC 1034, DOI 10.17487/RFC1034, November 1987,

   [RFC1035]  Mockapetris, P., "Domain names - implementation and
              specification", STD 13, RFC 1035, DOI 10.17487/RFC1035,
              November 1987, <>.

   [RFC1546]  Partridge, C., Mendez, T., and W. Milliken, "Host
              Anycasting Service", RFC 1546, DOI 10.17487/RFC1546,
              November 1993, <>.

   [RFC1995]  Ohta, M., "Incremental Zone Transfer in DNS", RFC 1995,
              DOI 10.17487/RFC1995, August 1996,

   [RFC1997]  Chandra, R., Traina, P., and T. Li, "BGP Communities
              Attribute", RFC 1997, DOI 10.17487/RFC1997, August 1996,

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   [RFC2181]  Elz, R. and R. Bush, "Clarifications to the DNS
              Specification", RFC 2181, DOI 10.17487/RFC2181, July 1997,

   [RFC4786]  Abley, J. and K. Lindqvist, "Operation of Anycast
              Services", BCP 126, RFC 4786, DOI 10.17487/RFC4786,
              December 2006, <>.

   [RFC5936]  Lewis, E. and A. Hoenes, Ed., "DNS Zone Transfer Protocol
              (AXFR)", RFC 5936, DOI 10.17487/RFC5936, June 2010,

   [RFC7094]  McPherson, D., Oran, D., Thaler, D., and E. Osterweil,
              "Architectural Considerations of IP Anycast", RFC 7094,
              DOI 10.17487/RFC7094, January 2014,

   [RFC8499]  Hoffman, P., Sullivan, A., and K. Fujiwara, "DNS
              Terminology", BCP 219, RFC 8499, DOI 10.17487/RFC8499,
              January 2019, <>.

   [RFC8782]  Reddy.K, T., Ed., Boucadair, M., Ed., Patil, P.,
              Mortensen, A., and N. Teague, "Distributed Denial-of-
              Service Open Threat Signaling (DOTS) Signal Channel
              Specification", RFC 8782, DOI 10.17487/RFC8782, May 2020,

   [RFC8783]  Boucadair, M., Ed. and T. Reddy.K, Ed., "Distributed
              Denial-of-Service Open Threat Signaling (DOTS) Data
              Channel Specification", RFC 8783, DOI 10.17487/RFC8783,
              May 2020, <>.

   [RFC8955]  Loibl, C., Hares, S., Raszuk, R., McPherson, D., and M.
              Bacher, "Dissemination of Flow Specification Rules",
              RFC 8955, DOI 10.17487/RFC8955, December 2020,

8.2.  Informative References

   [AnyBest]  Woodcock, B., "Best Practices in DNS Service-Provision
              Architecture", March 2016,

   [AnyFRoot] Woolf, S., "Anycasting", January 2003,

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   [AnyTest]  Schmidt, R.d.O., "Anycast Testbed", December 2018,

   [Ditl17]   OARC, D., "2017 DITL data", October 2018,

              ICANN, ., "DNS-STATS - Hedgehog 2.4.1", October 2018,

   [Jung03a]  Jung, J., Berger, A.W., and H. Balakrishnan, "Modeling
              TTL-based Internet caches", ACM 2003 IEEE INFOCOM,
              DOI 10.1109/INFCOM.2003.1208693, July 2003,

   [Moura16b] Moura, G.C.M., Schmidt, R.d.O., Heidemann, J., Mueller,
              M., Wei, L., and C. Hesselman, "Anycast vs DDoS Evaluating
              the November 2015 Root DNS Events.", ACM 2016 Internet
              Measurement Conference, DOI /10.1145/2987443.2987446, 14
              October 2016,

   [Moura18b] Moura, G.C.M., Heidemann, J., Mueller, M., Schmidt,
              R.d.O., and M. Davids, "When the Dike Breaks: Dissecting
              DNS Defenses During DDos", ACM 2018 Internet Measurement
              Conference, DOI 10.1145/3278532.3278534, 31 October 2018,

   [Moura19b] Moura, G., Hardaker, W., Heidemann, J., and R.d.O.
              Schmidt, "Cache Me If You Can: Effects of DNS Time-to-
              Live", ACM 2019 Internet Measurement Conference,
              DOI 10.1145/3355369.3355568, n.d.,

              Mueller, M., Moura, G.C.M., Schmidt, R.d.O., and J.
              Heidemann, "Recursives in the Wild- Engineering
              Authoritative DNS Servers.", ACM 2017 Internet Measurement
              Conference, DOI 10.1145/3131365.3131366, October 2017,

              Perlroth, N., "Hackers Used New Weapons to Disrupt Major
              Websites Across U.S.", October 2016,

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   [RFC4033]  Arends, R., Austein, R., Larson, M., Massey, D., and S.
              Rose, "DNS Security Introduction and Requirements",
              RFC 4033, DOI 10.17487/RFC4033, March 2005,

   [RFC4034]  Arends, R., Austein, R., Larson, M., Massey, D., and S.
              Rose, "Resource Records for the DNS Security Extensions",
              RFC 4034, DOI 10.17487/RFC4034, March 2005,

   [RFC4035]  Arends, R., Austein, R., Larson, M., Massey, D., and S.
              Rose, "Protocol Modifications for the DNS Security
              Extensions", RFC 4035, DOI 10.17487/RFC4035, March 2005,

   [RFC4509]  Hardaker, W., "Use of SHA-256 in DNSSEC Delegation Signer
              (DS) Resource Records (RRs)", RFC 4509,
              DOI 10.17487/RFC4509, May 2006,

   [RFC8811]  Mortensen, A., Ed., Reddy.K, T., Ed., Andreasen, F.,
              Teague, N., and R. Compton, "DDoS Open Threat Signaling
              (DOTS) Architecture", RFC 8811, DOI 10.17487/RFC8811,
              August 2020, <>.

              Staff, R.N., "RIPE Atlas A Global Internet Measurement
              Network", September 2015, <

              NCC, R., "Ripe Atlas - RIPE Network Coordination Centre",
              September 2019, <>.

              Schmidt, R.d.O., Heidemann, J., and J.H. Kuipers, "Anycast
              Latency - How Many Sites Are Enough. In Proceedings of the
              Passive and Active Measurement Workshop", PAM Passive and
              Active Measurement Conference, March 2017,

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              Singla, A., Chandrasekaran, B., Godfrey, P.B., and B.
              Maggs, "The Internet at the speed of light. In Proceedings
              of the 13th ACM Workshop on Hot Topics in Networks (Oct
              2014)", ACM Workshop on Hot Topics in Networks, October

   [VerfSrc]  Vries, W.d., "Verfploeter source code", November 2018,

   [Vries17b] Vries, W.d., Schmidt, R.d.O., Hardaker, W., Heidemann, J.,
              Boer, P.d., and A. Pras, "Verfploeter - Broad and Load-
              Aware Anycast Mapping", ACM 2017 Internet Measurement
              Conference, DOI 10.1145/3131365.3131371, October 2017,

Authors' Addresses

   Giovane C. M. Moura
   SIDN Labs/TU Delft
   Meander 501
   6825 MD Arnhem

   Phone: +31 26 352 5500

   Wes Hardaker
   USC/Information Sciences Institute
   PO Box 382
   Davis,  95617-0382
   United States of America

   Phone: +1 (530) 404-0099

   John Heidemann
   USC/Information Sciences Institute
   4676 Admiralty Way
   Marina Del Rey,  90292-6695
   United States of America

   Phone: +1 (310) 448-8708

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   Marco Davids
   SIDN Labs
   Meander 501
   6825 MD Arnhem

   Phone: +31 26 352 5500

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